r code for calculating beale’s f-type statistic: c1

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APPENDIX I R code for calculating Beale’s F-type Statistic: c1 <- 22 c2 <- 18 k1 <- c1^(-2/4) k2 <- c2^(-2/4) w1 <- 433.1 w2 <- 625.3 f <- ((w2-w1)/w1)*((70-c1)*k1)/((70-c2)*k2-(70-c1)*k1) print(f ) pf(0.95, df1=k2*(70-c2)-(70-c1)*k1, df2=k1*(70-c1)) f > pf(0.95, df1=k2*(70-c2)-(70-c1)*k1, df2=k1*(70-c1)) # if true, choose clustering with higher number of clusters

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Page 1: R Code for Calculating Beale’s F-Type Statistic: c1

APPENDIX I

R code for calculating Beale’s F-type Statistic:

c1 <- 22c2 <- 18k1 <- c1^(-2/4)k2 <- c2^(-2/4)w1 <- 433.1w2 <- 625.3 f <- ((w2-w1)/w1)*((70-c1)*k1)/((70-c2)*k2-(70-c1)*k1)print(f )pf(0.95, df1=k2*(70-c2)-(70-c1)*k1, df2=k1*(70-c1)) f > pf(0.95, df1=k2*(70-c2)-(70-c1)*k1, df2=k1*(70-c1))# if true, choose clustering with higher number of clusters

Page 2: R Code for Calculating Beale’s F-Type Statistic: c1

APPENDIX II- SAS OUPUT

MV EXAM2 18:24 Saturday, November 21, 2009 1

Obs newcopd newcvd newpneu newresp

1 64.2845 336.711 32.4186 97.2557 2 15.8351 160.462 16.8907 32.7258 3 21.5268 206.496 21.3919 42.9862 4 34.7171 161.644 12.1879 47.3974 5 47.6086 289.430 19.0434 66.9543 6 22.2840 370.108 19.8618 42.1459 7 29.5735 242.242 29.4285 59.1470 8 42.5145 427.039 31.8858 74.8212 9 31.7778 216.549 28.7582 60.8236 10 33.0126 328.191 31.1527 64.5372 11 53.2828 352.704 32.5355 85.8184 12 38.3076 427.984 24.1754 62.9135 13 47.7747 654.889 30.5973 78.3720 14 39.9447 273.252 19.6449 59.8703 15 43.7197 170.430 17.0236 62.0975 16 39.8540 256.660 23.5936 63.4475 17 48.6529 348.441 31.3024 81.7441 18 24.8226 323.218 21.1517 45.9743 19 40.8828 205.978 22.1123 63.2083 20 30.9771 216.197 15.8576 46.9062 21 29.8695 199.081 17.8040 47.9678 22 58.7476 588.639 31.4096 91.3205 23 35.6514 265.822 8.1310 44.1577 24 45.8040 288.686 23.2033 69.6100 25 35.8676 286.941 33.6041 70.6905 26 21.0847 201.672 12.5567 33.8766 27 29.9964 267.076 20.5999 50.5963 28 53.8088 322.272 26.2652 80.4227 29 31.8979 438.596 30.3030 62.2010 30 28.0800 278.665 16.9137 44.9936 31 55.0466 706.431 30.7999 86.5018 32 50.7304 310.738 29.3645 80.4236 33 41.8034 261.588 25.3354 67.1387 34 46.6951 738.682 18.5655 66.9483 35 53.1369 305.210 29.5787 83.2391 36 30.3803 265.544 14.2027 44.8035 37 27.2962 262.988 23.0967 50.3929 38 45.9381 254.913 19.9162 65.8543 39 41.8407 272.924 25.3347 67.1754 40 39.1544 361.180 14.3833 53.5377 41 34.8628 326.838 31.0496 65.9124 42 64.0135 380.188 35.3227 99.4804 43 74.4175 308.736 19.6418 94.0593 44 32.8701 356.000 26.1847 59.2776 45 35.9019 340.691 26.0500 62.0850 46 44.9667 293.738 14.7652 60.1794 47 38.7793 317.780 28.4265 68.0832 48 23.5229 349.159 31.2145 54.8382 49 32.9006 257.387 11.4286 44.4678 50 50.8746 383.376 33.1593 84.3367 51 52.4176 272.442 25.0224 78.0871

MV EXAM2 18:24 Saturday, November 21, 2009 2

Obs newcopd newcvd newpneu newresp

52 36.3085 374.485 31.4981 67.873 53 46.5798 256.498 24.3478 71.416 54 54.4604 472.666 39.9480 94.720 55 49.7610 301.931 9.9004 59.726 56 41.3568 274.214 17.8995 59.338

Page 3: R Code for Calculating Beale’s F-Type Statistic: c1

57 29.1472 272.160 20.6758 49.967 58 43.1137 234.815 7.3124 50.602 59 26.6851 206.765 11.6487 38.453 60 45.6529 352.098 27.9624 73.901 61 29.6878 231.775 12.3670 42.301 62 39.9208 443.437 36.1872 76.682 63 45.2450 324.345 13.1299 58.730 64 77.1583 483.894 32.4477 110.257 65 53.7047 326.410 30.3740 85.179 66 42.6643 271.254 18.9778 62.070 67 51.8546 302.518 14.9157 67.171 68 55.8176 391.162 23.5137 79.331 69 46.3710 269.394 18.7692 65.361 70 46.2073 306.806 38.0844 84.558

MV EXAM2 18:24 Saturday, November 21, 2009 3

Temp Temp Temp Obs April TempMay June July TempAug TempSep O3April

1 51.4000 61.6129 70.0667 76.0968 68.4516 63.7333 -2.59742 2 56.7667 67.4839 74.9333 83.2258 79.9032 70.2667 -5.77401 3 65.3667 69.1290 75.1667 79.3871 82.1290 73.3000 -4.00079 4 72.0000 76.6452 81.9667 83.4516 88.5161 81.6667 8.26811 5 58.0667 66.6452 73.9000 80.2258 77.8710 77.2333 2.01369 6 72.0333 74.7419 80.5000 81.8710 85.2903 76.3000 4.48913 7 49.4000 58.4194 71.2000 76.0323 71.6452 67.3667 6.72094 8 46.1333 59.8387 68.5667 74.5806 68.0645 64.4667 2.51458 9 62.2333 65.9677 73.6333 79.0645 79.6774 69.3667 0.53066 10 49.8000 61.8710 70.5667 78.5806 70.5484 63.6667 1.25153 11 55.3000 63.7742 73.2667 79.1935 72.9677 67.0667 -3.08945 12 50.5667 61.2581 70.4000 76.4194 69.3548 65.1667 -4.30625 13 68.2667 71.8548 78.3667 82.0323 84.3387 75.0833 -2.64460 14 55.1667 65.0323 74.7333 80.3548 73.3226 68.1000 -3.24023 15 42.5333 53.4839 63.0333 71.3226 69.0323 57.9000 8.53664 16 74.9000 78.8387 82.9667 82.9355 84.3871 79.8000 5.98796 17 53.8333 63.8065 72.7333 78.6452 71.5806 67.0000 -3.47475 18 53.1667 63.0000 71.1000 78.6774 75.6774 67.3333 2.21860 19 42.5917 54.3306 63.4167 73.1720 70.6452 58.9889 6.96790 20 68.2833 73.8871 82.1167 86.0484 90.2097 79.2667 3.47606 21 63.4333 74.3548 80.2333 81.3226 81.4839 75.6667 9.70463 22 58.0000 65.6452 74.7667 79.6452 74.6129 68.5000 -8.25527 23 58.7333 68.2258 76.2000 80.7097 78.6452 77.4333 4.01151

Obs O3May O3June O3July O3Aug O3Sep

1 2.9776 9.3160 10.1753 -1.3167 -5.4473 2 3.3453 6.7535 13.4359 8.1736 -6.5235 3 2.8535 -1.9897 -0.0305 13.6344 2.2994 4 2.1398 -5.5971 -11.3581 9.2746 11.6430 5 10.1284 14.0376 13.9645 9.5357 16.2752 6 13.4318 0.1609 -3.6472 8.2088 3.4473 7 2.6733 7.3469 7.7088 3.5155 -3.5027 8 9.0380 13.3186 15.9207 1.0480 0.3954 9 2.7441 4.2031 3.6292 12.7265 -6.9343 10 6.0385 7.6226 7.0373 -0.5158 0.0429 11 3.1260 4.7007 5.7707 0.9676 -4.9646 12 3.4514 9.1086 9.1632 0.2957 -4.3639 13 2.9716 -2.1978 -5.9310 7.2687 6.1511 14 5.2574 14.5176 7.3581 2.5967 -7.1603 15 8.9151 5.4381 5.8312 2.1564 -2.5394 16 4.8851 -5.2161 -13.0445 -5.0587 7.7383 17 2.9661 8.3600 8.3384 0.7234 -3.7851 18 10.2754 12.0268 19.8456 16.1971 1.9847 19 12.1597 8.0521 11.4697 6.8247 -1.1549 20 5.2499 1.2840 0.5819 19.9481 9.1287 21 9.3137 7.6609 5.2615 5.6874 0.4456 22 1.0679 2.0634 2.7001 2.6426 -0.4325

Page 4: R Code for Calculating Beale’s F-Type Statistic: c1

23 12.9835 14.8018 16.4152 9.8696 13.5157

MV EXAM2 18:24 Saturday, November 21, 2009 4

Temp Temp Temp Obs April TempMay June July TempAug TempSep O3April

24 51.5000 62.5806 71.6333 78.6129 69.7419 64.5667 -4.89325 25 49.0667 61.2258 69.5667 74.9032 68.0000 62.9667 -3.30959 26 73.1667 76.7742 82.1667 83.3226 87.0968 78.1667 6.53232 27 65.7667 69.4194 76.4667 80.7419 80.8387 74.0333 3.96797 28 55.2667 64.5484 74.0000 79.5161 72.6129 67.2667 -6.14490 29 69.5000 71.7742 79.7000 82.1935 84.2258 75.3667 0.10213 30 53.5667 63.5484 74.3667 81.0968 76.5484 69.5333 4.06688 31 47.8000 60.3226 69.7667 76.0000 69.0968 64.9333 0.84099 32 54.8000 63.6452 71.7667 81.1613 76.5484 65.9667 -1.13202 33 53.6667 64.3387 72.6167 82.0000 77.8871 65.8167 4.28449 34 53.0889 62.6237 73.0778 80.8710 75.8495 69.5667 8.25349 35 61.4000 66.3871 75.1333 78.8387 78.0000 70.1000 1.39910 36 58.8167 63.3871 65.6667 71.5161 70.0968 68.6000 5.58612 37 73.4000 76.9032 81.5667 82.5161 85.7419 78.4333 6.51440 38 61.2000 75.5806 85.4667 88.4194 88.1935 81.9333 8.86449 39 56.7000 65.5161 73.6667 79.8065 75.9355 68.9333 -6.40648 40 51.0667 61.8710 70.4000 80.8387 74.1935 64.1333 3.05017 41 72.2333 75.1290 80.7000 82.5484 86.0968 77.8667 6.32986 42 59.5000 67.8065 76.5000 83.4839 78.7742 72.2667 -1.95398 43 65.6833 71.1129 78.9000 84.4677 84.2097 75.1667 2.31853 44 67.2667 71.4194 79.9000 83.9355 82.9032 75.4333 -2.24268 45 78.0000 78.8387 81.0667 84.1613 83.8065 82.1000 7.48433 46 58.5167 64.8226 71.7333 74.3387 74.9032 73.4167 7.20520

Obs O3May O3June O3July O3Aug O3Sep

24 2.5078 6.7268 6.3050 -5.7237 -5.0256 25 3.9831 8.5222 7.1289 -6.8933 -9.5720 26 6.4918 -4.4637 -7.1414 7.2114 8.3122 27 9.1020 6.4593 3.3874 15.2416 10.0658 28 2.6241 4.6211 4.1704 -3.3937 -2.3107 29 3.5189 -2.0668 -5.8030 10.5212 1.5682 30 5.1239 11.9726 21.1476 9.2866 -2.5867 31 7.3021 5.8602 10.3271 -1.5896 -6.2976 32 5.7234 0.9810 5.5242 3.4300 -3.1669 33 10.5564 7.0183 11.9288 8.9702 1.9942 34 6.4617 7.5877 3.5178 -3.3418 -2.3785 35 5.3193 3.9502 -0.0561 7.6415 -0.0521 36 10.9744 9.0467 5.5017 5.2416 2.4389 37 8.3299 -2.7520 -5.1370 5.5211 3.6854 38 15.7920 15.3006 5.3280 5.5927 -0.3099 39 3.4592 3.4754 5.2706 7.5647 1.0119 40 3.8878 0.5766 1.2496 -3.6920 -2.7020 41 3.9044 -6.4831 -12.5135 3.5228 6.4176 42 3.5216 3.0344 3.9898 5.7273 -1.2057 43 8.3827 2.2919 0.9441 16.0051 5.4395 44 3.4254 0.2333 -1.4341 11.6956 1.0011 45 7.7844 -8.5097 -12.2927 -8.1683 -2.3517 46 10.4089 8.5813 12.2299 4.5215 7.4796

MV EXAM2 18:24 Saturday, November 21, 2009 5

Temp Temp Temp Obs April TempMay June July TempAug TempSep O3April

47 62.8333 67.9032 76.8000 82.1935 79.6129 72.0333 5.99371 48 53.0889 62.6237 73.0778 80.8710 75.8495 69.5667 -0.85701 49 54.8000 55.6774 59.8333 62.1935 64.0968 63.8667 9.22982 50 61.5333 68.3226 75.9000 82.4194 84.9677 71.3667 5.96884 51 51.5556 62.2581 70.8222 80.6882 73.3548 64.0889 -0.40624 52 53.8000 64.1613 73.1000 81.3871 77.7097 70.1667 7.16699

Page 5: R Code for Calculating Beale’s F-Type Statistic: c1

53 66.1333 80.0323 89.1333 91.4516 93.2258 87.6333 7.66572 54 52.1000 61.2581 69.6000 76.2581 69.1935 64.4000 -0.36179 55 62.9714 73.6037 79.1238 85.4378 84.6636 80.8048 5.01962 56 58.3267 64.2581 71.2067 73.6258 74.4387 73.2867 6.71122 57 71.4333 76.3548 82.0667 83.0968 86.4194 80.5667 6.96342 58 59.2889 66.7957 71.2667 76.7312 75.5054 72.8778 3.62120 59 54.8000 55.6774 59.8333 62.1935 64.0968 63.8667 8.75283 60 69.6333 72.1935 80.0333 83.1290 86.1290 75.5000 5.17327 61 58.8167 63.3871 65.6667 71.5161 70.0968 68.6000 9.37348 62 58.8000 67.0323 75.0667 83.1613 76.7419 69.9667 -0.48566 63 58.2222 64.5484 71.5667 74.1183 74.5161 73.0222 7.35334 64 74.6000 78.0323 81.4000 83.8065 84.0000 81.0333 9.64822 65 46.8333 60.9032 69.9667 75.1613 69.0968 65.1000 1.04130 66 48.7667 52.0968 58.3333 62.6774 65.0323 61.0333 7.19013 67 74.6000 78.0323 81.4000 83.8065 84.0000 81.0333 9.92602 68 50.9000 62.8387 71.0333 77.4516 69.9677 65.3333 -5.91671 69 56.2000 65.4516 73.3000 82.5161 81.4839 67.2333 5.00061

Obs O3May O3June O3July O3Aug O3Sep

47 8.8557 10.2495 5.6462 11.4303 5.2406 48 0.3905 7.4703 15.8371 6.1029 -3.1651 49 8.3519 0.9472 1.2300 -2.9679 0.5575 50 11.1463 2.9474 6.2657 20.3420 5.5170 51 0.8112 -0.8071 4.5477 -1.0881 6.4413 52 10.1299 10.4305 18.1820 10.9228 -1.0916 53 11.8096 8.4950 8.8198 9.5064 -0.6348 54 4.9377 10.6607 14.6198 2.4950 -2.8201 55 14.2865 15.4135 8.7508 8.3247 3.6302 56 7.9368 5.9901 7.9478 4.2798 8.0364 57 5.3762 -1.3773 -8.6641 2.1612 9.4445 58 12.9680 15.0344 8.3781 9.9923 1.1010 59 8.2189 -0.0051 1.6848 -3.9427 -1.0731 60 6.0310 1.6275 -0.7434 13.2357 3.1967 61 14.2964 10.1229 4.6612 6.4446 4.6599 62 4.1664 1.4408 8.4464 5.2479 -1.9683 63 8.1715 5.1208 7.3916 2.5567 5.3487 64 6.5928 -5.1627 -2.3514 -2.4759 1.1570 65 6.9690 12.5221 12.5066 -0.1769 1.0708 66 5.7665 -1.5010 -0.3845 -3.4556 -0.7950 67 7.3299 -4.6847 -3.0803 -2.3865 1.7117 68 -1.5588 9.1269 8.0693 -0.3838 -3.3277 69 10.3495 0.0144 9.1460 16.5816 3.6771

MV EXAM2 18:24 Saturday, November 21, 2009 6

Temp Temp Temp Obs April TempMay June July TempAug TempSep O3April

70 47.3889 58.7312 68.9111 73.3978 69.3441 65.3778 6.90519

Obs O3May O3June O3July O3Aug O3Sep

70 2.5181 8.5516 7.6622 -1.8237 -7.1056

MV EXAM2 18:24 Saturday, November 21, 2009 7

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

1 Akron 0 64.2845 336.711 32.4186 97.2557 51.4000 61.6129 70.0667 2 Arlington 1 15.8351 160.462 16.8907 32.7258 56.7667 67.4839 74.9333 3 Atlanta 1 21.5268 206.496 21.3919 42.9862 65.3667 69.1290 75.1667 4 Austin 1 34.7171 161.644 12.1879 47.3974 72.0000 76.6452 81.9667 5 Bakersfield 1 47.6086 289.430 19.0434 66.9543 58.0667 66.6452 73.9000 6 Baton Rouge 1 22.2840 370.108 19.8618 42.1459 72.0333 74.7419 80.5000 7 Boston 1 29.5735 242.242 29.4285 59.1470 49.4000 58.4194 71.2000

Page 6: R Code for Calculating Beale’s F-Type Statistic: c1

8 Buffalo 1 42.5145 427.039 31.8858 74.8212 46.1333 59.8387 68.5667 9 Charlotte 1 31.7778 216.549 28.7582 60.8236 62.2333 65.9677 73.6333 10 Chicago 0 33.0126 328.191 31.1527 64.5372 49.8000 61.8710 70.5667 11 Cincinnati 0 53.2828 352.704 32.5355 85.8184 55.3000 63.7742 73.2667 12 Cleveland 0 38.3076 427.984 24.1754 62.9135 50.5667 61.2581 70.4000 13 ColumbusGA 1 47.7747 654.889 30.5973 78.3720 68.2667 71.8548 78.3667 14 ColumbusOH 0 39.9447 273.252 19.6449 59.8703 55.1667 65.0323 74.7333 15 Colorado Springs 0 43.7197 170.430 17.0236 62.0975 42.5333 53.4839 63.0333 16 Corpus Christi 1 39.8540 256.660 23.5936 63.4475 74.9000 78.8387 82.9667 17 Dayton 0 48.6529 348.441 31.3024 81.7441 53.8333 63.8065 72.7333 18 Washington 0 24.8226 323.218 21.1517 45.9743 53.1667 63.0000 71.1000 19 Denver 0 40.8828 205.978 22.1123 63.2083 42.5917 54.3306 63.4167 20 Dallas/Fort Worth 1 30.9771 216.197 15.8576 46.9062 68.2833 73.8871 82.1167 21 El Paso 1 29.8695 199.081 17.8040 47.9678 63.4333 74.3548 80.2333 22 Evansville 0 58.7476 588.639 31.4096 91.3205 58.0000 65.6452 74.7667 23 Fresno 1 35.6514 265.822 8.1310 44.1577 58.7333 68.2258 76.2000

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

1 76.0968 68.4516 63.7333 -2.59742 2.9776 9.3160 10.1753 -1.3167 -5.4473 2 83.2258 79.9032 70.2667 -5.77401 3.3453 6.7535 13.4359 8.1736 -6.5235 3 79.3871 82.1290 73.3000 -4.00079 2.8535 -1.9897 -0.0305 13.6344 2.2994 4 83.4516 88.5161 81.6667 8.26811 2.1398 -5.5971 -11.3581 9.2746 11.6430 5 80.2258 77.8710 77.2333 2.01369 10.1284 14.0376 13.9645 9.5357 16.2752 6 81.8710 85.2903 76.3000 4.48913 13.4318 0.1609 -3.6472 8.2088 3.4473 7 76.0323 71.6452 67.3667 6.72094 2.6733 7.3469 7.7088 3.5155 -3.5027 8 74.5806 68.0645 64.4667 2.51458 9.0380 13.3186 15.9207 1.0480 0.3954 9 79.0645 79.6774 69.3667 0.53066 2.7441 4.2031 3.6292 12.7265 -6.9343 10 78.5806 70.5484 63.6667 1.25153 6.0385 7.6226 7.0373 -0.5158 0.0429 11 79.1935 72.9677 67.0667 -3.08945 3.1260 4.7007 5.7707 0.9676 -4.9646 12 76.4194 69.3548 65.1667 -4.30625 3.4514 9.1086 9.1632 0.2957 -4.3639 13 82.0323 84.3387 75.0833 -2.64460 2.9716 -2.1978 -5.9310 7.2687 6.1511 14 80.3548 73.3226 68.1000 -3.24023 5.2574 14.5176 7.3581 2.5967 -7.1603 15 71.3226 69.0323 57.9000 8.53664 8.9151 5.4381 5.8312 2.1564 -2.5394 16 82.9355 84.3871 79.8000 5.98796 4.8851 -5.2161 -13.0445 -5.0587 7.7383 17 78.6452 71.5806 67.0000 -3.47475 2.9661 8.3600 8.3384 0.7234 -3.7851 18 78.6774 75.6774 67.3333 2.21860 10.2754 12.0268 19.8456 16.1971 1.9847 19 73.1720 70.6452 58.9889 6.96790 12.1597 8.0521 11.4697 6.8247 -1.1549 20 86.0484 90.2097 79.2667 3.47606 5.2499 1.2840 0.5819 19.9481 9.1287 21 81.3226 81.4839 75.6667 9.70463 9.3137 7.6609 5.2615 5.6874 0.4456 22 79.6452 74.6129 68.5000 -8.25527 1.0679 2.0634 2.7001 2.6426 -0.4325 23 80.7097 78.6452 77.4333 4.01151 12.9835 14.8018 16.4152 9.8696 13.5157

MV EXAM2 18:24 Saturday, November 21, 2009 8

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

24 Fort Wayne 0 45.8040 288.686 23.2033 69.610 51.5000 62.5806 71.6333 25 Grand Rapids 0 35.8676 286.941 33.6041 70.690 49.0667 61.2258 69.5667 26 Houston 1 21.0847 201.672 12.5567 33.877 73.1667 76.7742 82.1667 27 Huntsville 1 29.9964 267.076 20.5999 50.596 65.7667 69.4194 76.4667 28 Indianapolis 0 53.8088 322.272 26.2652 80.423 55.2667 64.5484 74.0000 29 Jackson 1 31.8979 438.596 30.3030 62.201 69.5000 71.7742 79.7000 30 Jersey City 1 28.0800 278.665 16.9137 44.994 53.5667 63.5484 74.3667 31 Johnstown 0 55.0466 706.431 30.7999 86.502 47.8000 60.3226 69.7667 32 Kansas CityMO 0 50.7304 310.738 29.3645 80.424 54.8000 63.6452 71.7667 33 Kansas CityKS 0 41.8034 261.588 25.3354 67.139 53.6667 64.3387 72.6167 34 Kingston 1 46.6951 738.682 18.5655 66.948 53.0889 62.6237 73.0778 35 Knoxville 0 53.1369 305.210 29.5787 83.239 61.4000 66.3871 75.1333 36 Los Angeles 1 30.3803 265.544 14.2027 44.804 58.8167 63.3871 65.6667 37 Lafayette 1 27.2962 262.988 23.0967 50.393 73.4000 76.9032 81.5667 38 Las Vegas 0 45.9381 254.913 19.9162 65.854 61.2000 75.5806 85.4667 39 Lexington 0 41.8407 272.924 25.3347 67.175 56.7000 65.5161 73.6667 40 Lincoln 0 39.1544 361.180 14.3833 53.538 51.0667 61.8710 70.4000 41 Lake Charles 1 34.8628 326.838 31.0496 65.912 72.2333 75.1290 80.7000 42 Louisville 0 64.0135 380.188 35.3227 99.480 59.5000 67.8065 76.5000 43 Little Rock 0 74.4175 308.736 19.6418 94.059 65.6833 71.1129 78.9000

Page 7: R Code for Calculating Beale’s F-Type Statistic: c1

44 Memphis 0 32.8701 356.000 26.1847 59.278 67.2667 71.4194 79.9000 45 Miami 1 35.9019 340.691 26.0500 62.085 78.0000 78.8387 81.0667 46 Modesto 1 44.9667 293.738 14.7652 60.179 58.5167 64.8226 71.7333

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

24 78.6129 69.7419 64.5667 -4.89325 2.5078 6.7268 6.3050 -5.7237 -5.0256 25 74.9032 68.0000 62.9667 -3.30959 3.9831 8.5222 7.1289 -6.8933 -9.5720 26 83.3226 87.0968 78.1667 6.53232 6.4918 -4.4637 -7.1414 7.2114 8.3122 27 80.7419 80.8387 74.0333 3.96797 9.1020 6.4593 3.3874 15.2416 10.0658 28 79.5161 72.6129 67.2667 -6.14490 2.6241 4.6211 4.1704 -3.3937 -2.3107 29 82.1935 84.2258 75.3667 0.10213 3.5189 -2.0668 -5.8030 10.5212 1.5682 30 81.0968 76.5484 69.5333 4.06688 5.1239 11.9726 21.1476 9.2866 -2.5867 31 76.0000 69.0968 64.9333 0.84099 7.3021 5.8602 10.3271 -1.5896 -6.2976 32 81.1613 76.5484 65.9667 -1.13202 5.7234 0.9810 5.5242 3.4300 -3.1669 33 82.0000 77.8871 65.8167 4.28449 10.5564 7.0183 11.9288 8.9702 1.9942 34 80.8710 75.8495 69.5667 8.25349 6.4617 7.5877 3.5178 -3.3418 -2.3785 35 78.8387 78.0000 70.1000 1.39910 5.3193 3.9502 -0.0561 7.6415 -0.0521 36 71.5161 70.0968 68.6000 5.58612 10.9744 9.0467 5.5017 5.2416 2.4389 37 82.5161 85.7419 78.4333 6.51440 8.3299 -2.7520 -5.1370 5.5211 3.6854 38 88.4194 88.1935 81.9333 8.86449 15.7920 15.3006 5.3280 5.5927 -0.3099 39 79.8065 75.9355 68.9333 -6.40648 3.4592 3.4754 5.2706 7.5647 1.0119 40 80.8387 74.1935 64.1333 3.05017 3.8878 0.5766 1.2496 -3.6920 -2.7020 41 82.5484 86.0968 77.8667 6.32986 3.9044 -6.4831 -12.5135 3.5228 6.4176 42 83.4839 78.7742 72.2667 -1.95398 3.5216 3.0344 3.9898 5.7273 -1.2057 43 84.4677 84.2097 75.1667 2.31853 8.3827 2.2919 0.9441 16.0051 5.4395 44 83.9355 82.9032 75.4333 -2.24268 3.4254 0.2333 -1.4341 11.6956 1.0011 45 84.1613 83.8065 82.1000 7.48433 7.7844 -8.5097 -12.2927 -8.1683 -2.3517 46 74.3387 74.9032 73.4167 7.20520 10.4089 8.5813 12.2299 4.5215 7.4796

MV EXAM2 18:24 Saturday, November 21, 2009 9

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

47 Nashville 0 38.7793 317.780 28.4265 68.083 62.8333 67.9032 76.8000 48 New York 1 23.5229 349.159 31.2145 54.838 53.0889 62.6237 73.0778 49 Oakland 1 32.9006 257.387 11.4286 44.468 54.8000 55.6774 59.8333 50 Oklahoma City 0 50.8746 383.376 33.1593 84.337 61.5333 68.3226 75.9000 51 Omaha 0 52.4176 272.442 25.0224 78.087 51.5556 62.2581 70.8222 52 Philadelphia 0 36.3085 374.485 31.4981 67.873 53.8000 64.1613 73.1000 53 Phoenix 0 46.5798 256.498 24.3478 71.416 66.1333 80.0323 89.1333 54 Pittsburgh 0 54.4604 472.666 39.9480 94.720 52.1000 61.2581 69.6000 55 Riverside 1 49.7610 301.931 9.9004 59.726 62.9714 73.6037 79.1238 56 Sacramento 1 41.3568 274.214 17.8995 59.338 58.3267 64.2581 71.2067 57 San Antonio 1 29.1472 272.160 20.6758 49.967 71.4333 76.3548 82.0667 58 San Bernardino 1 43.1137 234.815 7.3124 50.602 59.2889 66.7957 71.2667 59 San Jose 1 26.6851 206.765 11.6487 38.453 54.8000 55.6774 59.8333 60 Shreveport 1 45.6529 352.098 27.9624 73.901 69.6333 72.1935 80.0333 61 Santa Ana/Anaheim 1 29.6878 231.775 12.3670 42.301 58.8167 63.3871 65.6667 62 St. Louis 0 39.9208 443.437 36.1872 76.682 58.8000 67.0323 75.0667 63 Stockton 1 45.2450 324.345 13.1299 58.730 58.2222 64.5484 71.5667 64 St. Petersburg 1 77.1583 483.894 32.4477 110.257 74.6000 78.0323 81.4000 65 Syracuse 1 53.7047 326.410 30.3740 85.179 46.8333 60.9032 69.9667 66 Tacoma 1 42.6643 271.254 18.9778 62.070 48.7667 52.0968 58.3333 67 Tampa 1 51.8546 302.518 14.9157 67.171 74.6000 78.0323 81.4000 68 Toledo 0 55.8176 391.162 23.5137 79.331 50.9000 62.8387 71.0333 69 Wichita 0 46.3710 269.394 18.7692 65.361 56.2000 65.4516 73.3000

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

47 82.1935 79.6129 72.0333 5.99371 8.8557 10.2495 5.6462 11.4303 5.2406 48 80.8710 75.8495 69.5667 -0.85701 0.3905 7.4703 15.8371 6.1029 -3.1651 49 62.1935 64.0968 63.8667 9.22982 8.3519 0.9472 1.2300 -2.9679 0.5575 50 82.4194 84.9677 71.3667 5.96884 11.1463 2.9474 6.2657 20.3420 5.5170 51 80.6882 73.3548 64.0889 -0.40624 0.8112 -0.8071 4.5477 -1.0881 6.4413 52 81.3871 77.7097 70.1667 7.16699 10.1299 10.4305 18.1820 10.9228 -1.0916

Page 8: R Code for Calculating Beale’s F-Type Statistic: c1

53 91.4516 93.2258 87.6333 7.66572 11.8096 8.4950 8.8198 9.5064 -0.6348 54 76.2581 69.1935 64.4000 -0.36179 4.9377 10.6607 14.6198 2.4950 -2.8201 55 85.4378 84.6636 80.8048 5.01962 14.2865 15.4135 8.7508 8.3247 3.6302 56 73.6258 74.4387 73.2867 6.71122 7.9368 5.9901 7.9478 4.2798 8.0364 57 83.0968 86.4194 80.5667 6.96342 5.3762 -1.3773 -8.6641 2.1612 9.4445 58 76.7312 75.5054 72.8778 3.62120 12.9680 15.0344 8.3781 9.9923 1.1010 59 62.1935 64.0968 63.8667 8.75283 8.2189 -0.0051 1.6848 -3.9427 -1.0731 60 83.1290 86.1290 75.5000 5.17327 6.0310 1.6275 -0.7434 13.2357 3.1967 61 71.5161 70.0968 68.6000 9.37348 14.2964 10.1229 4.6612 6.4446 4.6599 62 83.1613 76.7419 69.9667 -0.48566 4.1664 1.4408 8.4464 5.2479 -1.9683 63 74.1183 74.5161 73.0222 7.35334 8.1715 5.1208 7.3916 2.5567 5.3487 64 83.8065 84.0000 81.0333 9.64822 6.5928 -5.1627 -2.3514 -2.4759 1.1570 65 75.1613 69.0968 65.1000 1.04130 6.9690 12.5221 12.5066 -0.1769 1.0708 66 62.6774 65.0323 61.0333 7.19013 5.7665 -1.5010 -0.3845 -3.4556 -0.7950 67 83.8065 84.0000 81.0333 9.92602 7.3299 -4.6847 -3.0803 -2.3865 1.7117 68 77.4516 69.9677 65.3333 -5.91671 -1.5588 9.1269 8.0693 -0.3838 -3.3277 69 82.5161 81.4839 67.2333 5.00061 10.3495 0.0144 9.1460 16.5816 3.6771

MV EXAM2 18:24 Saturday, November 21, 2009 10

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

70 Worcester 1 46.2073 306.806 38.0844 84.558 47.3889 58.7312 68.9111

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

70 73.3978 69.3441 65.3778 6.90519 2.5181 8.5516 7.6622 -1.8237 -7.1056

MV EXAM2 18:24 Saturday, November 21, 2009 11

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 4 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

Within Covariance Matrix Information

Natural Log of the Covariance Determinant of the coast Matrix Rank Covariance Matrix

0 4 15.57201 1 4 15.47987 Pooled 4 15.80345

MV EXAM2 18:24 Saturday, November 21, 2009 12

The DISCRIM Procedure Test of Homogeneity of Within Covariance Matrices

Notation: K = Number of Groups

P = Number of Variables

N = Total Number of Observations - Number of Groups

Page 9: R Code for Calculating Beale’s F-Type Statistic: c1

N(i) = Number of Observations in the i'th Group - 1

__ N(i)/2 || |Within SS Matrix(i)| V = ----------------------------------- N/2 |Pooled SS Matrix|

_ _ 2 | 1 1 | 2P + 3P - 1 RHO = 1.0 - | SUM ----- - --- | ------------- |_ N(i) N _| 6(P+1)(K-1)

DF = .5(K-1)P(P+1) _ _ | PN/2 | | N V | Under the null hypothesis: -2 RHO ln | ------------------ | | __ PN(i)/2 | |_ || N(i) _|

is distributed approximately as Chi-Square(DF).

Chi-Square DF Pr > ChiSq

17.923615 10 0.0563

Since the Chi-Square value is significant at the 0.1 level, the within covariance matrices will be used in the discriminant function. Reference: Morrison, D.F. (1976) Multivariate Statistical Methods p252.

MV EXAM2 18:24 Saturday, November 21, 2009 13

The DISCRIM Procedure

Pairwise Generalized Squared Distances Between Groups

2 _ _ -1 _ _ D (i|j) = (X - X )' COV (X - X ) + ln |COV | i j j i j j

Generalized Squared Distance to coast

From coast 0 1

0 15.57201 16.84623 1 17.37277 15.47987

MV EXAM2 18:24 Saturday, November 21, 2009 14

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.GENERAL Resubstitution Summary using Quadratic Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) + ln |COV | j j j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Page 10: R Code for Calculating Beale’s F-Type Statistic: c1

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 22 10 32 68.75 31.25 100.00

1 6 32 38 15.79 84.21 100.00

Total 28 42 70 40.00 60.00 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.3125 0.1579 0.2352 Priors 0.5000 0.5000

MV EXAM2 18:24 Saturday, November 21, 2009 15 Effect of Coast on Mortality

The GLM Procedure

Number of Observations Read 70 Number of Observations Used 70

MV EXAM2 18:24 Saturday, November 21, 2009 16 Effect of Coast on Mortality

The GLM Procedure Multivariate Analysis of Variance

E = Error SSCP Matrix

newcopd newcvd newpneu newresp

newcopd 8462.4470383 33646.228809 1190.5009748 9726.0940452 newcvd 33646.228809 849528.93547 24206.838565 58676.169704 newpneu 1190.5009748 24206.838565 3543.0990866 4755.8275604 newresp 9726.0940452 58676.169704 4755.8275604 14587.381199

Partial Correlation Coefficients from the Error SSCP Matrix / Prob > |r|

DF = 68 newcopd newcvd newpneu newresp

newcopd 1.000000 0.396825 0.217415 0.875390 0.0007 0.0727 <.0001

newcvd 0.396825 1.000000 0.441222 0.527089 0.0007 0.0001 <.0001

newpneu 0.217415 0.441222 1.000000 0.661524 0.0727 0.0001 <.0001

newresp 0.875390 0.527089 0.661524 1.000000 <.0001 <.0001 <.0001

MV EXAM2 18:24 Saturday, November 21, 2009 17 Effect of Coast on Mortality

The GLM Procedure Multivariate Analysis of Variance

Page 11: R Code for Calculating Beale’s F-Type Statistic: c1

H = Type III SSCP Matrix for coast

newcopd newcvd newpneu newresp

newcopd 1768.2279153 6593.3637208 1119.0089599 2917.2991868 newcvd 6593.3637208 24585.317752 4172.5577432 10878.017735 newpneu 1119.0089599 4172.5577432 708.15591226 1846.1895668 newresp 2917.2991868 10878.017735 1846.1895668 4813.0868605

Characteristic Roots and Vectors of: E Inverse * H, where H = Type III SSCP Matrix for coast E = Error SSCP Matrix

Characteristic Characteristic Vector V'EV=1 Root Percent newcopd newcvd newpneu newresp

0.37951828 100.00 -0.06036113 -0.00040115 -0.05571805 0.06774461 0.00000000 0.00 -0.32885220 -0.00017496 -0.32745291 0.32532213 0.00000000 0.00 -0.00338330 0.00117676 0.00133345 -0.00112040 0.00000000 0.00 -0.00596076 -0.00038217 0.01580911 -0.00158734

MANOVA Test Criteria and Exact F Statistics for the Hypothesis of No Overall coast Effect H = Type III SSCP Matrix for coast E = Error SSCP Matrix

S=1 M=1 N=31.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.72489072 6.17 4 65 0.0003 Pillai's Trace 0.27510928 6.17 4 65 0.0003 Hotelling-Lawley Trace 0.37951828 6.17 4 65 0.0003 Roy's Greatest Root 0.37951828 6.17 4 65 0.0003

H = Type III SSCP Matrix for Intercept

newcopd newcvd newpneu newresp

newcopd 70464.399683 513957.07904 40484.286518 111591.03139 newcvd 513957.07904 3748728.1561 295286.49559 813928.74701 newpneu 40484.286518 295286.49559 23259.652566 64112.989086 newresp 111591.03139 813928.74701 64112.989086 176721.27122

MV EXAM2 18:24 Saturday, November 21, 2009 18 Effect of Coast on Mortality

The GLM Procedure Multivariate Analysis of Variance

Characteristic Roots and Vectors of: E Inverse * H, where H = Type III SSCP Matrix for Intercept E = Error SSCP Matrix

Characteristic Characteristic Vector V'EV=1 Root Percent newcopd newcvd newpneu newresp

12.3556739 100.00 0.02139226 0.00011282 0.02318113 -0.01407612 0.0000000 0.00 -0.01084949 0.00112044 -0.00308131 0.00280836 0.0000000 0.00 -0.01208734 -0.00062723 0.00919855 0.00718428 0.0000000 0.00 -0.33333582 -0.00024662 -0.33158730 0.33191860

MANOVA Test Criteria and Exact F Statistics for the Hypothesis of No Overall Intercept Effect H = Type III SSCP Matrix for Intercept E = Error SSCP Matrix

Page 12: R Code for Calculating Beale’s F-Type Statistic: c1

S=1 M=1 N=31.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.07487454 200.78 4 65 <.0001 Pillai's Trace 0.92512546 200.78 4 65 <.0001 Hotelling-Lawley Trace 12.35567394 200.78 4 65 <.0001 Roy's Greatest Root 12.35567394 200.78 4 65 <.0001

MV EXAM2 18:24 Saturday, November 21, 2009 19 Effect of Coast on Mortality

The MEANS Procedure

N coast Obs Variable N Mean Std Dev Minimum Maximum ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 0 32 newcopd 32 46.9256059 10.4654806 24.8226145 74.4175238 newcvd 32 342.2685421 104.0352160 170.4295948 706.4312769 newpneu 32 26.9604181 6.1229006 14.3832579 39.9480052 newresp 32 74.3137923 13.2431913 45.9742789 99.4803952

1 38 newcopd 38 36.8365308 11.7025433 15.8350620 77.1583167 newcvd 38 304.6484248 117.8645380 160.4619615 738.6820742 newpneu 38 20.5756272 8.0217809 7.3123619 38.0844329 newresp 38 57.6683982 15.7261493 32.7257948 110.2571727 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ

MV EXAM2 18:24 Saturday, November 21, 2009 20 Effect of Coast on Mortality

Obs city coast res1 res2 res3 res4

1 Akron 0 17.3589 -5.558 5.4581 22.9419 2 Chicago 0 -13.9130 -14.077 4.1923 -9.7766 3 Cincinnati 0 6.3572 10.436 5.5751 11.5046 4 Cleveland 0 -8.6180 85.715 -2.7850 -11.4003 5 ColumbusOH 0 -6.9809 -69.017 -7.3155 -14.4435 6 Colorado Springs 0 -3.2059 -171.839 -9.9368 -12.2163 7 Dayton 0 1.7273 6.172 4.3420 7.4303 8 Washington 0 -22.1030 -19.050 -5.8088 -28.3395 9 Denver 0 -6.0428 -136.290 -4.8482 -11.1055 10 Evansville 0 11.8220 246.370 4.4492 17.0067 11 Fort Wayne 0 -1.1216 -53.583 -3.7571 -4.7038 12 Grand Rapids 0 -11.0580 -55.328 6.6437 -3.6233 13 Indianapolis 0 6.8832 -19.997 -0.6952 6.1089 14 Johnstown 0 8.1210 364.163 3.8395 12.1880 15 Kansas CityMO 0 3.8048 -31.531 2.4041 6.1098 16 Kansas CityKS 0 -5.1222 -80.681 -1.6250 -7.1750 17 Knoxville 0 6.2113 -37.059 2.6183 8.9253 18 Las Vegas 0 -0.9875 -87.356 -7.0442 -8.4595 19 Lexington 0 -5.0849 -69.344 -1.6257 -7.1384 20 Lincoln 0 -7.7712 18.911 -12.5772 -20.7761 21 Louisville 0 17.0879 37.920 8.3623 25.1666 22 Little Rock 0 27.4919 -33.533 -7.3186 19.7455 23 Memphis 0 -14.0555 13.731 -0.7758 -15.0362 24 Nashville 0 -8.1463 -24.488 1.4661 -6.2306 25 Oklahoma City 0 3.9490 41.108 6.1989 10.0229 26 Omaha 0 5.4920 -69.827 -1.9380 3.7733 27 Philadelphia 0 -10.6171 32.217 4.5377 -6.4412 28 Phoenix 0 -0.3458 -85.771 -2.6126 -2.8980 29 Pittsburgh 0 7.5348 130.398 12.9876 20.4067 30 St. Louis 0 -7.0048 101.169 9.2268 2.3687 31 Toledo 0 8.8919 48.894 -3.4467 5.0175 32 Wichita 0 -0.5546 -72.875 -8.1912 -8.9527 33 Arlington 1 -21.0015 -144.186 -3.6849 -24.9426 34 Atlanta 1 -15.3097 -98.153 0.8162 -14.6822 35 Austin 1 -2.1194 -143.005 -8.3877 -10.2709

Page 13: R Code for Calculating Beale’s F-Type Statistic: c1

36 Bakersfield 1 10.7721 -15.218 -1.5322 9.2859 37 Baton Rouge 1 -14.5525 65.460 -0.7138 -15.5225 38 Boston 1 -7.2630 -62.407 8.8529 1.4786 39 Buffalo 1 5.6779 122.390 11.3102 17.1528 40 Charlotte 1 -5.0587 -88.099 8.1826 3.1552 41 ColumbusGA 1 10.9382 350.241 10.0217 20.7036 42 Corpus Christi 1 3.0174 -47.989 3.0179 5.7791 43 Dallas/Fort Worth 1 -5.8594 -88.451 -4.7180 -10.7622 44 El Paso 1 -6.9670 -105.567 -2.7716 -9.7006 45 Fresno 1 -1.1851 -38.826 -12.4446 -13.5107 46 Houston 1 -15.7519 -102.977 -8.0189 -23.7918 47 Huntsville 1 -6.8401 -37.572 0.0243 -7.0721 48 Jackson 1 -4.9386 133.948 9.7274 4.5326 49 Jersey City 1 -8.7566 -25.983 -3.6620 -12.6748 50 Kingston 1 9.8585 434.034 -2.0101 9.2799

MV EXAM2 18:24 Saturday, November 21, 2009 21 Effect of Coast on Mortality

Obs city coast res1 res2 res3 res4

51 Los Angeles 1 -6.4563 -39.105 -6.3730 -12.8649 52 Lafayette 1 -9.5404 -41.660 2.5211 -7.2755 53 Lake Charles 1 -1.9738 22.190 10.4740 8.2440 54 Miami 1 -0.9346 36.043 5.4743 4.4166 55 Modesto 1 8.1302 -10.910 -5.8104 2.5110 56 New York 1 -13.3137 44.511 10.6389 -2.8302 57 Oakland 1 -3.9359 -47.262 -9.1470 -13.2006 58 Riverside 1 12.9245 -2.718 -10.6752 2.0577 59 Sacramento 1 4.5203 -30.435 -2.6761 1.6696 60 San Antonio 1 -7.6894 -32.488 0.1002 -7.7018 61 San Bernardino 1 6.2772 -69.834 -13.2633 -7.0669 62 San Jose 1 -10.1514 -97.883 -8.9269 -19.2157 63 Shreveport 1 8.8163 47.449 7.3867 16.2322 64 Santa Ana/Anaheim 1 -7.1488 -72.873 -8.2086 -15.3677 65 Stockton 1 8.4085 19.696 -7.4457 1.0614 66 St. Petersburg 1 40.3218 179.246 11.8721 52.5888 67 Syracuse 1 16.8682 21.762 9.7984 27.5109 68 Tacoma 1 5.8278 -33.395 -1.5979 4.4017 69 Tampa 1 15.0180 -2.130 -5.6599 9.5023 70 Worcester 1 9.3708 2.158 17.5088 26.8897

MULTNORM macro: Univariate and Multivariate Normality Tests 22 18:24 Saturday, November 21, 2009

The MODEL Procedure

Normality Test Equation Test Statistic Value Prob

res1 Shapiro-Wilk W 0.96 0.0947 res2 Shapiro-Wilk W 0.83 <.0001 res3 Shapiro-Wilk W 0.97 0.1579 res4 Shapiro-Wilk W 0.96 0.1232 System Mardia Skewness 139.4 <.0001 Mardia Kurtosis 7.95 <.0001 Henze-Zirkler T 6.83 <.0001

MULTNORM macro: Chi-square Q-Q plot 23 18:24 Saturday, November 21, 2009

Plot of mahdist*chisq. Legend: A = 1 obs, B = 2 obs, etc.

‚ 30 ˆ ‚ ‚ A ‚ ‚

Page 14: R Code for Calculating Beale’s F-Type Statistic: c1

‚ ‚ 25 ˆ ‚ ‚ ‚ ‚ ‚S ‚q 20 ˆu ‚a ‚r ‚e ‚d ‚ ‚D 15 ˆi ‚ A As ‚t ‚ Aa ‚ A A An ‚c ‚e 10 ˆ ‚ A ‚ A ‚ A ‚ A ‚ ‚ AA 5 ˆ AA A ‚ BAA ‚ ABAAA ‚ BABBAB ‚ BBB ‚ BBCBBBB ‚ A ABABBBB 0 ˆ Šƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒ 0 2 4 6 8 10 12 14

Chi-square quantile

18:24 Saturday, November 21, 2009 24 PCA for Monthly Average Temperature

The PRINCOMP Procedure

Observations 70 Variables 6

Simple Statistics

TempApril TempMay TempJune TempJuly TempAug TempSep

Mean 58.94818708 66.59422317 74.11575284 79.25106210 77.18855826 70.98567120 StD 8.63420426 6.63610816 6.05594370 5.36009810 6.95429017 6.41753881

Covariance Matrix

TempApril TempMay TempJune TempJuly TempAug TempSep

TempApril 74.54948326 52.73167090 41.46605954 26.32568310 50.19128481 48.74207506 TempMay 52.73167090 44.03793148 37.99894263 28.17872912 42.23109172 39.88678788 TempJune 41.46605954 37.99894263 36.67445406 29.53024667 38.84360144 34.19826478 TempJuly 26.32568310 28.17872912 29.53024667 28.73065163 31.35367184 23.69063811

Page 15: R Code for Calculating Beale’s F-Type Statistic: c1

TempAug 50.19128481 42.23109172 38.84360144 31.35367184 48.36215179 39.40518827 TempSep 48.74207506 39.88678788 34.19826478 23.69063811 39.40518827 41.18480436

Total Variance 273.53947658

Eigenvalues of the Covariance Matrix

Eigenvalue Difference Proportion Cumulative

1 240.547597 218.394415 0.8794 0.8794 2 22.153182 17.060157 0.0810 0.9604 3 5.093025 0.955167 0.0186 0.9790 4 4.137857 3.200044 0.0151 0.9941 5 0.937814 0.267811 0.0034 0.9976 6 0.670003 0.0024 1.0000

18:24 Saturday, November 21, 2009 25 PCA for Monthly Average Temperature

The PRINCOMP Procedure

Eigenvectors

Prin1 Prin2 Prin3 Prin4 Prin5 Prin6

TempApril 0.516475 -.647457 -.431514 0.123839 0.197359 0.271225 TempMay 0.422504 -.025767 0.065324 0.381422 -.192403 -.796277 TempJune 0.371905 0.328773 0.075812 0.328594 -.623603 0.500992 TempJuly 0.279665 0.639452 -.232952 0.218592 0.638239 0.059077 TempAug 0.429021 0.217752 -.224042 -.812513 -.196741 -.139449 TempSep 0.392631 -.125417 0.836253 -.152471 0.298485 0.135834

18:24 Saturday, November 21, 2009 26 PCA for Monthly Average Temperature

The FACTOR Procedure Initial Factor Method: Principal Components

Prior Communality Estimates: ONE

Eigenvalues of the Correlation Matrix: Total = 6 Average = 1

Eigenvalue Difference Proportion Cumulative

1 5.25001474 4.73909181 0.8750 0.8750 2 0.51092293 0.40330129 0.0852 0.9602 3 0.10762164 0.01748935 0.0179 0.9781 4 0.09013229 0.06373441 0.0150 0.9931 5 0.02639787 0.01148734 0.0044 0.9975 6 0.01491054 0.0025 1.0000

1 factor will be retained by the MINEIGEN criterion.

18:24 Saturday, November 21, 2009 27 PCA for Monthly Average Temperature

The FACTOR Procedure Initial Factor Method: Principal Components

Scree Plot of Eigenvalues

Page 16: R Code for Calculating Beale’s F-Type Statistic: c1

6 ˆ ‚ ‚ ‚ ‚ ‚ 1 ‚ 5 ˆ ‚ ‚ ‚ ‚ ‚ ‚ 4 ˆ ‚E ‚i ‚g ‚e ‚n ‚v 3 ˆa ‚l ‚u ‚e ‚s ‚ ‚ 2 ˆ ‚ ‚ ‚ ‚ ‚ ‚ 1 ˆ ‚ ‚ ‚ 2 ‚ ‚ ‚ 3 4 0 ˆ 5 6 Šƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒ 0 1 2 3 4 5 6

Number

18:24 Saturday, November 21, 2009 28 PCA for Monthly Average Temperature

The FACTOR Procedure Initial Factor Method: Principal Components

Factor Pattern

Factor1

TempApril 0.89270 TempMay 0.98337 TempJune 0.97189 TempJuly 0.85385 TempAug 0.96272 TempSep 0.94107

Variance Explained by Each Factor

Factor1

Page 17: R Code for Calculating Beale’s F-Type Statistic: c1

5.2500147

Final Communality Estimates: Total = 5.250015

TempApril TempMay TempJune TempJuly TempAug TempSep

0.79691806 0.96700837 0.94457202 0.72906184 0.92683842 0.88561603

18:24 Saturday, November 21, 2009 29 PCA for Monthly Average Ozone

The PRINCOMP Procedure

Observations 70 Variables 6

Simple Statistics

O3April O3May O3June O3July O3Aug O3Sep

Mean 2.867204331 6.606144213 4.862347903 4.839117060 4.860274651 1.093176544 StD 4.870968343 3.802739068 5.979171119 7.597983938 6.535203562 5.260907195

Covariance Matrix

O3April O3May O3June O3July O3Aug O3Sep

O3April 23.72633260 11.39312798 -3.85632986 -7.72979788 1.36407039 9.64344898 O3May 11.39312798 14.46082442 7.99450540 5.73552664 7.70482402 7.02882174 O3June -3.85632986 7.99450540 35.75048727 37.59784422 4.71539086 -6.10625848 O3July -7.72979788 5.73552664 37.59784422 57.72935992 7.81740222 -11.01889795 O3Aug 1.36407039 7.70482402 4.71539086 7.81740222 42.70888559 14.98348097 O3Sep 9.64344898 7.02882174 -6.10625848 -11.01889795 14.98348097 27.67714451

Total Variance 202.05303431

Eigenvalues of the Covariance Matrix

Eigenvalue Difference Proportion Cumulative

1 91.4204695 34.1181979 0.4525 0.4525 2 57.3022716 27.7307075 0.2836 0.7361 3 29.5715640 17.1594150 0.1464 0.8824 4 12.4121490 4.6460029 0.0614 0.9438 5 7.7661461 4.1857120 0.0384 0.9823 6 3.5804341 0.0177 1.0000

18:24 Saturday, November 21, 2009 30 PCA for Monthly Average Ozone

The PRINCOMP Procedure

Eigenvectors

Prin1 Prin2 Prin3 Prin4 Prin5 Prin6

O3April -.124969 0.289350 0.699708 -.375257 0.271089 0.443577 O3May 0.098041 0.297491 0.422217 -.159242 -.318382 -.772589 O3June 0.574772 0.020593 0.195581 0.208177 -.646820 0.411396

Page 18: R Code for Calculating Beale’s F-Type Statistic: c1

O3July 0.773086 -.025798 0.033534 0.044283 0.612052 -.154855 O3Aug 0.141406 0.731448 -.530701 -.382715 -.062154 0.114064 O3Sep -.163555 0.540065 0.105453 0.801283 0.168218 0.010352

18:24 Saturday, November 21, 2009 31 PCA for Monthly Average Ozone

The FACTOR Procedure Initial Factor Method: Principal Components

Prior Communality Estimates: ONE

Eigenvalues of the Correlation Matrix: Total = 6 Average = 1

Eigenvalue Difference Proportion Cumulative

1 2.09525561 0.02916709 0.3492 0.3492 2 2.06608852 1.02899216 0.3443 0.6936 3 1.03709635 0.62520164 0.1728 0.8664 4 0.41189472 0.15859958 0.0686 0.9351 5 0.25329514 0.11692547 0.0422 0.9773 6 0.13636967 0.0227 1.0000

3 factors will be retained by the MINEIGEN criterion.

18:24 Saturday, November 21, 2009 32 PCA for Monthly Average Ozone

The FACTOR Procedure Initial Factor Method: Principal Components

Scree Plot of Eigenvalues ‚ ‚ ‚ ‚ 2.5 ˆ ‚ ‚ ‚ ‚ ‚ ‚ 1 2 2.0 ˆ ‚ ‚ ‚ ‚E ‚i ‚g 1.5 ˆe ‚n ‚v ‚a ‚l ‚u ‚ 3e 1.0 ˆs ‚ ‚ ‚ ‚ ‚ ‚ 0.5 ˆ

Page 19: R Code for Calculating Beale’s F-Type Statistic: c1

‚ 4 ‚ ‚ 5 ‚ ‚ 6 ‚ 0.0 ˆ ‚ ‚ ‚ Šƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒ 0 1 2 3 4 5 6

Number

18:24 Saturday, November 21, 2009 33 PCA for Monthly Average Ozone

The FACTOR Procedure Initial Factor Method: Principal Components

Factor Pattern

Factor1 Factor2 Factor3

O3April 0.73088 -0.25121 -0.54093 O3May 0.83665 0.28204 -0.30873 O3June 0.10673 0.93991 -0.08205 O3July -0.00900 0.94529 0.01804 O3Aug 0.56551 0.17983 0.72067 O3Sep 0.72788 -0.33779 0.35036

Variance Explained by Each Factor

Factor1 Factor2 Factor3

2.0952556 2.0660885 1.0370964

Final Communality Estimates: Total = 5.198440

O3April O3May O3June O3July O3Aug O3Sep

0.88989918 0.87484780 0.90155177 0.89397063 0.87151343 0.76665766

18:24 Saturday, November 21, 2009 34 Data with PC scores from Temp and Ozone

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July TempAug

1 Akron 0 64.2845 336.711 32.4186 97.2557 51.4000 61.6129 70.0667 76.0968 68.4516 2 Arlington 1 15.8351 160.462 16.8907 32.7258 56.7667 67.4839 74.9333 83.2258 79.9032 3 Atlanta 1 21.5268 206.496 21.3919 42.9862 65.3667 69.1290 75.1667 79.3871 82.1290 4 Austin 1 34.7171 161.644 12.1879 47.3974 72.0000 76.6452 81.9667 83.4516 88.5161 5 Bakersfield 1 47.6086 289.430 19.0434 66.9543 58.0667 66.6452 73.9000 80.2258 77.8710 6 Baton Rouge 1 22.2840 370.108 19.8618 42.1459 72.0333 74.7419 80.5000 81.8710 85.2903 7 Boston 1 29.5735 242.242 29.4285 59.1470 49.4000 58.4194 71.2000 76.0323 71.6452 8 Buffalo 1 42.5145 427.039 31.8858 74.8212 46.1333 59.8387 68.5667 74.5806 68.0645 9 Charlotte 1 31.7778 216.549 28.7582 60.8236 62.2333 65.9677 73.6333 79.0645 79.6774 10 Chicago 0 33.0126 328.191 31.1527 64.5372 49.8000 61.8710 70.5667 78.5806 70.5484

Obs TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2 PCT3

1 63.7333 -2.59742 2.9776 9.3160 10.1753 -1.3167 -5.4473 -14.9869 0.67431 -0.74777 2 70.2667 -5.77401 3.3453 6.7535 13.4359 8.1736 -6.5235 1.5472 4.88127 -1.07394 3 73.3000 -4.00079 2.8535 -1.9897 -0.0305 13.6344 2.2994 7.8431 -3.00296 -1.72760

Page 20: R Code for Calculating Beale’s F-Type Statistic: c1

4 81.6667 8.26811 2.1398 -5.5971 -11.3581 9.2746 11.6430 24.1355 -2.31523 1.03536 5 77.2333 2.01369 10.1284 14.0376 13.9645 9.5357 16.2752 2.5044 0.48683 5.21203 6 76.3000 4.48913 13.4318 0.1609 -3.6472 8.2088 3.4473 18.8700 -3.81007 -2.61150 7 67.3667 6.72094 2.6733 7.3469 7.7088 3.5155 -3.5027 -14.1691 2.62259 2.33049 8 64.4667 2.51458 9.0380 13.3186 15.9207 1.0480 0.3954 -19.3166 2.49105 2.34841 9 69.3667 0.53066 2.7441 4.2031 3.6292 12.7265 -6.9343 1.6325 -1.64374 -3.36313 10 63.6667 1.25153 6.0385 7.6226 7.0373 -0.5158 0.0429 -13.9503 3.92124 -1.10673

Obs PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

1 3.34990 -0.46525 -0.06240 7.2086 -10.7570 -1.7173 0.9151 -0.65715 0.61300 2 -0.88940 0.67658 -1.13189 10.2075 -5.3432 -9.3266 -2.8348 1.24694 -1.56791 3 -2.23032 -0.07069 -0.11761 -6.1692 3.9501 -12.4227 -0.8587 0.44206 -1.19877 4 -1.88439 -0.61332 -0.41074 -20.7477 9.3629 -1.9257 2.5538 1.23829 4.66429 5 -1.45462 2.30347 0.42333 10.9585 12.3735 2.1102 12.4493 0.56094 -0.04786 6 0.00562 -1.30199 0.00649 -8.7079 6.3426 1.2839 -2.4453 -3.69869 -4.76767 7 -0.90634 -0.53725 2.55027 3.3409 -3.5435 1.8472 -3.3435 1.75667 5.12471 8 1.39937 -0.90051 -0.76557 13.2850 -2.6556 4.7551 2.8961 0.56255 -0.71447 9 -1.80680 -0.02224 0.57017 1.0243 -0.3890 -8.4562 -8.1418 -1.55721 2.67765 10 2.26395 0.01041 -0.60606 2.8437 -5.1358 1.9857 2.5846 -0.53973 -0.10706

18:24 Saturday, November 21, 2009 35 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Dependent Variable: newcopd

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 13 3047.71424 234.43956 1.83 0.0610 Error 56 7182.96071 128.26716 Corrected Total 69 10231

Root MSE 11.32551 R-Square 0.2979 Dependent Mean 41.44868 Adj R-Sq 0.1349 Coeff Var 27.32417

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 20.28952 30.21802 0.67 0.5047 TempApril 1 -0.19539 0.96740 -0.20 0.8407 TempMay 1 -0.48570 1.67049 -0.29 0.7723 TempJune 1 -0.16807 1.57222 -0.11 0.9153 TempJuly 1 1.12896 1.19635 0.94 0.3494 TempAug 1 -1.52321 1.66760 -0.91 0.3649 TempSep 1 1.61922 1.07314 1.51 0.1370 O3April 1 0.15609 0.51604 0.30 0.7634 O3May 1 -0.03675 0.81499 -0.05 0.9642 O3June 1 -0.31666 0.69463 -0.46 0.6502 O3July 1 -0.16258 0.51643 -0.31 0.7541 O3Aug 1 -0.15963 0.66349 -0.24 0.8107 O3Sep 1 0.29670 0.38927 0.76 0.4491 coast 1 -12.50162 4.65428 -2.69 0.0095

18:24 Saturday, November 21, 2009 36

Page 21: R Code for Calculating Beale’s F-Type Statistic: c1

Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Dependent Variable: newcvd

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 13 236190 18168 1.59 0.1143 Error 56 637924 11391 Corrected Total 69 874114

Root MSE 106.73096 R-Square 0.2702 Dependent Mean 321.84619 Adj R-Sq 0.1008 Coeff Var 33.16210

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 -193.94372 284.77292 -0.68 0.4986 TempApril 1 10.72090 9.11669 1.18 0.2446 TempMay 1 -39.54714 15.74261 -2.51 0.0149 TempJune 1 26.74436 14.81647 1.81 0.0764 TempJuly 1 22.51034 11.27431 2.00 0.0507 TempAug 1 -24.88893 15.71541 -1.58 0.1189 TempSep 1 8.86207 10.11322 0.88 0.3846 O3April 1 -5.95457 4.86311 -1.22 0.2259 O3May 1 14.62094 7.68038 1.90 0.0621 O3June 1 -9.52123 6.54615 -1.45 0.1514 O3July 1 -0.69330 4.86684 -0.14 0.8872 O3Aug 1 -1.42830 6.25265 -0.23 0.8201 O3Sep 1 -0.95663 3.66843 -0.26 0.7952 coast 1 39.53147 43.86164 0.90 0.3713

18:24 Saturday, November 21, 2009 37 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Dependent Variable: newpneu

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 13 2030.33507 156.17962 3.94 0.0002 Error 56 2220.91993 39.65928 Corrected Total 69 4251.25500

Root MSE 6.29756 R-Square 0.4776 Dependent Mean 23.49439 Adj R-Sq 0.3563 Coeff Var 26.80454

Page 22: R Code for Calculating Beale’s F-Type Statistic: c1

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 18.99406 16.80276 1.13 0.2631 TempApril 1 0.32595 0.53792 0.61 0.5470 TempMay 1 -0.98947 0.92888 -1.07 0.2913 TempJune 1 2.39558 0.87423 2.74 0.0082 TempJuly 1 0.19842 0.66523 0.30 0.7666 TempAug 1 -1.37459 0.92727 -1.48 0.1438 TempSep 1 -0.47947 0.59672 -0.80 0.4251 O3April 1 0.15236 0.28694 0.53 0.5975 O3May 1 -0.13786 0.45317 -0.30 0.7621 O3June 1 -0.54554 0.38625 -1.41 0.1634 O3July 1 0.17302 0.28716 0.60 0.5493 O3Aug 1 0.29330 0.36893 0.80 0.4300 O3Sep 1 -0.30819 0.21645 -1.42 0.1600 coast 1 -1.39572 2.58802 -0.54 0.5918

18:24 Saturday, November 21, 2009 38 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Dependent Variable: newresp

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 13 7402.54091 569.42622 2.66 0.0058 Error 56 11998 214.24870 Corrected Total 69 19400

Root MSE 14.63724 R-Square 0.3816 Dependent Mean 65.27772 Adj R-Sq 0.2380 Coeff Var 22.42302

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 40.02573 39.05417 1.02 0.3098 TempApril 1 0.12833 1.25028 0.10 0.9186 TempMay 1 -1.50822 2.15896 -0.70 0.4877 TempJune 1 2.27612 2.03195 1.12 0.2674 TempJuly 1 1.33574 1.54617 0.86 0.3913 TempAug 1 -2.91614 2.15523 -1.35 0.1815 TempSep 1 1.12797 1.38694 0.81 0.4195 O3April 1 0.32036 0.66693 0.48 0.6329 O3May 1 -0.17657 1.05330 -0.17 0.8675 O3June 1 -0.85262 0.89775 -0.95 0.3463 O3July 1 0.00097820 0.66745 0.00 0.9988 O3Aug 1 0.11777 0.85750 0.14 0.8913 O3Sep 1 -0.00352 0.50309 -0.01 0.9944 coast 1 -13.97280 6.01525 -2.32 0.0238

18:24 Saturday, November 21, 2009 39

Page 23: R Code for Calculating Beale’s F-Type Statistic: c1

Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 1

Error Matrix (E)

7182.9607091 26200.250916 1232.2889422 8466.6544963 26200.250916 637923.87939 14196.002201 40972.094964 1232.2889422 14196.002201 2220.9199306 3462.4529769 8466.6544963 40972.094964 3462.4529769 11997.927153

Hypothesis Matrix (H)

3047.7142445 14039.341614 1077.2209926 4176.7387357 14039.341614 236190.37383 14183.394107 28582.092475 1077.2209926 14183.394107 2030.3350682 3139.5641502 4176.7387357 28582.092475 3139.5641502 7402.5409062

Multivariate Statistics and F Approximations

S=4 M=4 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.24917223 1.72 52 207.38 0.0041 Pillai's Trace 1.11977412 1.67 52 224 0.0057 Hotelling-Lawley Trace 1.78180977 1.77 52 145.56 0.0042 Roy's Greatest Root 0.95974748 4.13 13 56 <.0001

NOTE: F Statistic for Roy's Greatest Root is an upper bound.

18:24 Saturday, November 21, 2009 40 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 2

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.96444398 0.49 4 53 0.7441 Pillai's Trace 0.03555602 0.49 4 53 0.7441 Hotelling-Lawley Trace 0.03686686 0.49 4 53 0.7441 Roy's Greatest Root 0.03686686 0.49 4 53 0.7441

18:24 Saturday, November 21, 2009 41 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 3

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.88980204 1.64 4 53 0.1777 Pillai's Trace 0.11019796 1.64 4 53 0.1777 Hotelling-Lawley Trace 0.12384548 1.64 4 53 0.1777

Page 24: R Code for Calculating Beale’s F-Type Statistic: c1

Roy's Greatest Root 0.12384548 1.64 4 53 0.1777

18:24 Saturday, November 21, 2009 42 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 4

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.84234630 2.48 4 53 0.0549 Pillai's Trace 0.15765370 2.48 4 53 0.0549 Hotelling-Lawley Trace 0.18716019 2.48 4 53 0.0549 Roy's Greatest Root 0.18716019 2.48 4 53 0.0549

18:24 Saturday, November 21, 2009 43 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 5

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.92653793 1.05 4 53 0.3901 Pillai's Trace 0.07346207 1.05 4 53 0.3901 Hotelling-Lawley Trace 0.07928662 1.05 4 53 0.3901 Roy's Greatest Root 0.07928662 1.05 4 53 0.3901

18:24 Saturday, November 21, 2009 44 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 6

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.94200591 0.82 4 53 0.5209 Pillai's Trace 0.05799409 0.82 4 53 0.5209 Hotelling-Lawley Trace 0.06156447 0.82 4 53 0.5209 Roy's Greatest Root 0.06156447 0.82 4 53 0.5209

18:24 Saturday, November 21, 2009 45 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 7

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Page 25: R Code for Calculating Beale’s F-Type Statistic: c1

Wilks' Lambda 0.91390002 1.25 4 53 0.3019 Pillai's Trace 0.08609998 1.25 4 53 0.3019 Hotelling-Lawley Trace 0.09421160 1.25 4 53 0.3019 Roy's Greatest Root 0.09421160 1.25 4 53 0.3019

18:24 Saturday, November 21, 2009 46 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 8

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.93289162 0.95 4 53 0.4409 Pillai's Trace 0.06710838 0.95 4 53 0.4409 Hotelling-Lawley Trace 0.07193588 0.95 4 53 0.4409 Roy's Greatest Root 0.07193588 0.95 4 53 0.4409

18:24 Saturday, November 21, 2009 47 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 9

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.91007588 1.31 4 53 0.2785 Pillai's Trace 0.08992412 1.31 4 53 0.2785 Hotelling-Lawley Trace 0.09880948 1.31 4 53 0.2785 Roy's Greatest Root 0.09880948 1.31 4 53 0.2785

18:24 Saturday, November 21, 2009 48 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 10

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.93923011 0.86 4 53 0.4956 Pillai's Trace 0.06076989 0.86 4 53 0.4956 Hotelling-Lawley Trace 0.06470181 0.86 4 53 0.4956 Roy's Greatest Root 0.06470181 0.86 4 53 0.4956

18:24 Saturday, November 21, 2009 49 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 11

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Page 26: R Code for Calculating Beale’s F-Type Statistic: c1

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.98410336 0.21 4 53 0.9295 Pillai's Trace 0.01589664 0.21 4 53 0.9295 Hotelling-Lawley Trace 0.01615343 0.21 4 53 0.9295 Roy's Greatest Root 0.01615343 0.21 4 53 0.9295

18:24 Saturday, November 21, 2009 50 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 12

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.97481245 0.34 4 53 0.8481 Pillai's Trace 0.02518755 0.34 4 53 0.8481 Hotelling-Lawley Trace 0.02583835 0.34 4 53 0.8481 Roy's Greatest Root 0.02583835 0.34 4 53 0.8481

18:24 Saturday, November 21, 2009 51 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 13

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.93532901 0.92 4 53 0.4615 Pillai's Trace 0.06467099 0.92 4 53 0.4615 Hotelling-Lawley Trace 0.06914251 0.92 4 53 0.4615 Roy's Greatest Root 0.06914251 0.92 4 53 0.4615

18:24 Saturday, November 21, 2009 52 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 14

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=25.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.82519020 2.81 4 53 0.0346 Pillai's Trace 0.17480980 2.81 4 53 0.0346 Hotelling-Lawley Trace 0.21184182 2.81 4 53 0.0346 Roy's Greatest Root 0.21184182 2.81 4 53 0.0346

18:24 Saturday, November 21, 2009 53 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Dependent Variable: newcopd

Page 27: R Code for Calculating Beale’s F-Type Statistic: c1

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 7 2691.18077 384.45440 3.16 0.0064 Error 62 7539.49419 121.60474 Corrected Total 69 10231

Root MSE 11.02745 R-Square 0.2631 Dependent Mean 41.44868 Adj R-Sq 0.1798 Coeff Var 26.60508

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 48.11297 2.35922 20.39 <.0001 PCT1 1 0.13659 0.14265 0.96 0.3420 PCT2 1 -0.02778 0.45660 -0.06 0.9517 PCO1 1 -0.01593 0.23089 -0.07 0.9452 PCO2 1 -0.26565 0.22445 -1.18 0.2411 PCO3 1 0.41358 0.26720 1.55 0.1268 PCO4 1 0.69546 0.37992 1.83 0.0720 coast 1 -12.27632 3.60446 -3.41 0.0012

18:24 Saturday, November 21, 2009 54 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Dependent Variable: newcvd

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 7 106907 15272 1.23 0.2981 Error 62 767207 12374 Corrected Total 69 874114

Root MSE 111.23989 R-Square 0.1223 Dependent Mean 321.84619 Adj R-Sq 0.0232 Coeff Var 34.56306

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 328.24533 23.79872 13.79 <.0001 PCT1 1 0.88349 1.43895 0.61 0.5415 PCT2 1 2.34210 4.60600 0.51 0.6129 PCO1 1 0.03544 2.32912 0.02 0.9879 PCO2 1 -4.82485 2.26414 -2.13 0.0371

Page 28: R Code for Calculating Beale’s F-Type Statistic: c1

PCO3 1 -0.93247 2.69542 -0.35 0.7306 PCO4 1 2.95725 3.83243 0.77 0.4433 coast 1 -11.78788 36.36016 -0.32 0.7469

18:24 Saturday, November 21, 2009 55 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Dependent Variable: newpneu

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 7 1539.98653 219.99808 5.03 0.0001 Error 62 2711.26847 43.73014 Corrected Total 69 4251.25500

Root MSE 6.61288 R-Square 0.3622 Dependent Mean 23.49439 Adj R-Sq 0.2902 Coeff Var 28.14662

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 24.82633 1.41476 17.55 <.0001 PCT1 1 0.02900 0.08554 0.34 0.7358 PCT2 1 0.27819 0.27381 1.02 0.3136 PCO1 1 -0.04426 0.13846 -0.32 0.7503 PCO2 1 -0.38240 0.13460 -2.84 0.0061 PCO3 1 -0.36996 0.16023 -2.31 0.0243 PCO4 1 -0.24137 0.22783 -1.06 0.2935 coast 1 -2.45358 2.16150 -1.14 0.2607

18:24 Saturday, November 21, 2009 56 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Dependent Variable: newresp

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 7 6433.51824 919.07403 4.39 0.0005 Error 62 12967 209.14435 Corrected Total 69 19400

Root MSE 14.46182 R-Square 0.3316 Dependent Mean 65.27772 Adj R-Sq 0.2562 Coeff Var 22.15430

Page 29: R Code for Calculating Beale’s F-Type Statistic: c1

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 73.31611 3.09397 23.70 <.0001 PCT1 1 0.16035 0.18707 0.86 0.3947 PCT2 1 0.26899 0.59881 0.45 0.6548 PCO1 1 -0.06609 0.30280 -0.22 0.8280 PCO2 1 -0.65850 0.29435 -2.24 0.0289 PCO3 1 0.05854 0.35042 0.17 0.8679 PCO4 1 0.46664 0.49824 0.94 0.3526 coast 1 -14.80757 4.72703 -3.13 0.0026

18:24 Saturday, November 21, 2009 57 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Multivariate Test 15

Error Matrix (E)

7539.4941866 29085.936933 1285.9646192 8876.7069283 29085.936933 767207.46523 17876.798444 47584.083796 1285.9646192 17876.798444 2711.268467 4013.9030106 8876.7069283 47584.083796 4013.9030106 12966.949821

Hypothesis Matrix (H)

2691.1807669 11153.655597 1023.5453156 3766.6863037 11153.655597 106906.78799 10502.597864 21970.103643 1023.5453156 10502.597864 1539.9865318 2588.1141165 3766.6863037 21970.103643 2588.1141165 6433.5182383

Multivariate Statistics and F Approximations

S=4 M=1 N=28.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.40016927 2.21 28 214.15 0.0008 Pillai's Trace 0.77299870 2.12 28 248 0.0013 Hotelling-Lawley Trace 1.10449325 2.28 28 138.03 0.0009 Roy's Greatest Root 0.61881147 5.48 7 62 <.0001

NOTE: F Statistic for Roy's Greatest Root is an upper bound.

18:24 Saturday, November 21, 2009 58 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Multivariate Test 16

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=28.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.95476897 0.70 4 59 0.5959 Pillai's Trace 0.04523103 0.70 4 59 0.5959 Hotelling-Lawley Trace 0.04737379 0.70 4 59 0.5959 Roy's Greatest Root 0.04737379 0.70 4 59 0.5959

Page 30: R Code for Calculating Beale’s F-Type Statistic: c1

18:24 Saturday, November 21, 2009 59 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Multivariate Test 17

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=28.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.95974123 0.62 4 59 0.6509 Pillai's Trace 0.04025877 0.62 4 59 0.6509 Hotelling-Lawley Trace 0.04194752 0.62 4 59 0.6509 Roy's Greatest Root 0.04194752 0.62 4 59 0.6509

18:24 Saturday, November 21, 2009 60 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Multivariate Test 18

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=28.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.98808517 0.18 4 59 0.9490 Pillai's Trace 0.01191483 0.18 4 59 0.9490 Hotelling-Lawley Trace 0.01205851 0.18 4 59 0.9490 Roy's Greatest Root 0.01205851 0.18 4 59 0.9490

18:24 Saturday, November 21, 2009 61 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Multivariate Test 19

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=28.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.86059448 2.39 4 59 0.0610 Pillai's Trace 0.13940552 2.39 4 59 0.0610 Hotelling-Lawley Trace 0.16198747 2.39 4 59 0.0610 Roy's Greatest Root 0.16198747 2.39 4 59 0.0610

18:24 Saturday, November 21, 2009 62 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Multivariate Test 20

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=28.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.82493451 3.13 4 59 0.0211 Pillai's Trace 0.17506549 3.13 4 59 0.0211

Page 31: R Code for Calculating Beale’s F-Type Statistic: c1

Hotelling-Lawley Trace 0.21221745 3.13 4 59 0.0211 Roy's Greatest Root 0.21221745 3.13 4 59 0.0211

18:24 Saturday, November 21, 2009 63 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Multivariate Test 21

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=28.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.90040515 1.63 4 59 0.1783 Pillai's Trace 0.09959485 1.63 4 59 0.1783 Hotelling-Lawley Trace 0.11061116 1.63 4 59 0.1783 Roy's Greatest Root 0.11061116 1.63 4 59 0.1783

18:24 Saturday, November 21, 2009 64 Regression Model Using PC Scores

The REG Procedure Model: MODEL2 Multivariate Test 22

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=28.5

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.82627376 3.10 4 59 0.0220 Pillai's Trace 0.17372624 3.10 4 59 0.0220 Hotelling-Lawley Trace 0.21025263 3.10 4 59 0.0220 Roy's Greatest Root 0.21025263 3.10 4 59 0.0220

18:24 Saturday, November 21, 2009 65 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Dependent Variable: newcopd

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 2 1982.23971 991.11986 8.05 0.0007 Error 67 8248.43524 123.11097 Corrected Total 69 10231

Root MSE 11.09554 R-Square 0.1938 Dependent Mean 41.44868 Adj R-Sq 0.1697 Coeff Var 26.76934

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Page 32: R Code for Calculating Beale’s F-Type Statistic: c1

Intercept 1 47.53327 2.01485 23.59 <.0001 PCO3 1 0.33993 0.25782 1.32 0.1918 coast 1 -11.20846 2.79424 -4.01 0.0002

18:24 Saturday, November 21, 2009 66 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Dependent Variable: newcvd

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 2 27557 13779 1.09 0.3419 Error 67 846557 12635 Corrected Total 69 874114

Root MSE 112.40632 R-Square 0.0315 Dependent Mean 321.84619 Adj R-Sq 0.0026 Coeff Var 34.92548

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 340.00412 20.41201 16.66 <.0001 PCO3 1 -1.26673 2.61194 -0.48 0.6293 coast 1 -33.44881 28.30781 -1.18 0.2415

18:24 Saturday, November 21, 2009 67 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Dependent Variable: newpneu

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 2 973.00012 486.50006 9.94 0.0002 Error 67 3278.25487 48.92918 Corrected Total 69 4251.25500

Root MSE 6.99494 R-Square 0.2289 Dependent Mean 23.49439 Adj R-Sq 0.2059 Coeff Var 29.77281

Parameter Estimates

Parameter Standard

Page 33: R Code for Calculating Beale’s F-Type Statistic: c1

Variable DF Estimate Error t Value Pr > |t|

Intercept 1 26.28443 1.27022 20.69 <.0001 PCO3 1 -0.37815 0.16254 -2.33 0.0230 coast 1 -5.13954 1.76157 -2.92 0.0048

18:24 Saturday, November 21, 2009 68 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Dependent Variable: newresp

Number of Observations Read 70 Number of Observations Used 70

Analysis of Variance

Sum of Mean Source DF Squares Square F Value Pr > F

Model 2 4813.98986 2406.99493 11.06 <.0001 Error 67 14586 217.70863 Corrected Total 69 19400

Root MSE 14.75495 R-Square 0.2481 Dependent Mean 65.27772 Adj R-Sq 0.2257 Coeff Var 22.60335

Parameter Estimates

Parameter Standard Variable DF Estimate Error t Value Pr > |t|

Intercept 1 74.27432 2.67937 27.72 <.0001 PCO3 1 -0.02208 0.34285 -0.06 0.9488 coast 1 -16.57268 3.71581 -4.46 <.0001

18:24 Saturday, November 21, 2009 69 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 1

Error Matrix (E)

8248.4352399 34443.727254 1428.5761439 9739.9955879 34443.727254 846557.11908 23319.669827 58624.366679 1428.5761439 23319.669827 3278.2548744 4740.3629358 9739.9955879 58624.366679 4740.3629358 14586.478198

Hypothesis Matrix (H)

1982.2397136 5795.8652761 880.93379085 2903.3976441 5795.8652761 27557.134138 5059.7264811 10929.82076 880.93379085 5059.7264811 973.00012443 1861.6541914 2903.3976441 10929.82076 1861.6541914 4813.9898616

Multivariate Statistics and F Approximations

S=2 M=0.5 N=31

Statistic Value F Value Num DF Den DF Pr > F

Page 34: R Code for Calculating Beale’s F-Type Statistic: c1

Wilks' Lambda 0.60171700 4.63 8 128 <.0001 Pillai's Trace 0.44493264 4.65 8 130 <.0001 Hotelling-Lawley Trace 0.58438328 4.63 8 89.135 <.0001 Roy's Greatest Root 0.38078287 6.19 4 65 0.0003

NOTE: F Statistic for Roy's Greatest Root is an upper bound. NOTE: F Statistic for Wilks' Lambda is exact.

18:24 Saturday, November 21, 2009 70 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 2

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=31

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.83007961 3.28 4 64 0.0166 Pillai's Trace 0.16992039 3.28 4 64 0.0166 Hotelling-Lawley Trace 0.20470373 3.28 4 64 0.0166 Roy's Greatest Root 0.20470373 3.28 4 64 0.0166

18:24 Saturday, November 21, 2009 71 Regression Model Using PC Scores

The REG Procedure Model: MODEL1 Multivariate Test 3

Multivariate Statistics and Exact F Statistics

S=1 M=1 N=31

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.73775886 5.69 4 64 0.0006 Pillai's Trace 0.26224114 5.69 4 64 0.0006 Hotelling-Lawley Trace 0.35545645 5.69 4 64 0.0006 Roy's Greatest Root 0.35545645 5.69 4 64 0.0006

MULTNORM macro: Univariate and Multivariate Normality Tests 72 18:24 Saturday, November 21, 2009

The MODEL Procedure

Normality Test Equation Test Statistic Value Prob

res1 Shapiro-Wilk W 0.96 0.0580 res2 Shapiro-Wilk W 0.83 <.0001 res3 Shapiro-Wilk W 0.97 0.2716 res4 Shapiro-Wilk W 0.96 0.1260 System Mardia Skewness 137.5 <.0001 Mardia Kurtosis 7.52 <.0001 Henze-Zirkler T 6.79 <.0001

MULTNORM macro: Chi-square Q-Q plot 73 18:24 Saturday, November 21, 2009

Plot of mahdist*chisq. Legend: A = 1 obs, B = 2 obs, etc.

‚ 30 ˆ ‚

Page 35: R Code for Calculating Beale’s F-Type Statistic: c1

‚ ‚ ‚ A ‚ ‚ 25 ˆ ‚ ‚ ‚ ‚ ‚S ‚q 20 ˆu ‚a ‚r ‚e ‚d ‚ ‚D 15 ˆ Ai ‚s ‚ A At ‚a ‚ An ‚ Ac ‚e 10 ˆ A ‚ A A ‚ A A ‚ ‚ ‚ ‚ AA 5 ˆ A A ‚ AAAA ‚ AABAAAA ‚ AABBAA ‚ BBBA ‚ BBCBBBB ‚ A ABABBBB 0 ˆ Šƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒˆƒƒ 0 2 4 6 8 10 12 14

Chi-square quantile

18:24 Saturday, November 21, 2009 74 Plots of first two PC's to determine Number of Clusters

Plot of PCT1*PCT2. Legend: A = 1 obs, B = 2 obs, etc.

PCT1 ‚ ‚ 40 ˆ ‚ ‚ ‚ ‚ A 30 ˆ ‚ ‚ A ‚ C A ‚ A AA A 20 ˆ A A ‚ A ‚ A A A ‚ A A A ‚ A 10 ˆ

Page 36: R Code for Calculating Beale’s F-Type Statistic: c1

‚ AA A ‚ A ‚ A A ‚ A A A A 0 ˆ A A ‚ A A A ‚ A B A AA ‚ AA A B A ‚ A A -10 ˆ B A A ‚ A A ‚ AA A A A ‚ A ‚ AA A -20 ˆ A ‚ ‚ ‚ B A ‚ A -30 ˆ ‚ A ‚ ‚ ‚ -40 ˆ ‚ Šƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒ -15 -10 -5 0 5 10

PCT2

18:24 Saturday, November 21, 2009 75 Plots of first two PC's to determine Number of Clusters

Plot of PCO1*PCO2. Legend: A = 1 obs, B = 2 obs, etc.

PCO1 ‚ ‚ 20 ˆ ‚ ‚ A A ‚ 15 ˆ A ‚ A A ‚ ‚ A A A 10 ˆ A A A A ‚ A ‚ A A A ‚ A A B 5 ˆ A A AA ‚ A A A ‚ A A A A A ‚ A A B A A A A A 0 ˆ A A ‚ A A A ‚ A ‚ A A -5 ˆ A A ‚ A A A A A A ‚ ‚ A A -10 ˆ ‚ A ‚ A A ‚ AA -15 ˆ ‚ A A ‚

Page 37: R Code for Calculating Beale’s F-Type Statistic: c1

‚ -20 ˆ ‚ A A ‚ A A ‚ -25 ˆ ‚ Šˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒ -20 -15 -10 -5 0 5 10 15 20

PCO2

18:24 Saturday, November 21, 2009 76 Clustering based on Monthly Average Temperatures

The CLUSTER Procedure Average Linkage Cluster Analysis

Eigenvalues of the Covariance Matrix

Eigenvalue Difference Proportion Cumulative

1 240.547597 218.394415 0.8794 0.8794 2 22.153182 17.060157 0.0810 0.9604 3 5.093025 0.955167 0.0186 0.9790 4 4.137857 3.200044 0.0151 0.9941 5 0.937814 0.267811 0.0034 0.9976 6 0.670003 0.0024 1.0000

Root-Mean-Square Total-Sample Standard Deviation = 6.75203 Root-Mean-Square Distance Between Observations = 23.38972

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

69 Kingston New York 2 0.0000 1.00 . . . . 0 T 68 Oakland San Jose 2 0.0000 1.00 . . . . 0 T 67 Los Angeles Santa Ana/Anaheim 2 0.0000 1.00 . . . . 0 T 66 St. Petersburg Tampa 2 0.0000 1.00 . . . . 0 65 Sacramento Stockton 2 0.0000 1.00 . . 5429 . 0.0315 64 Modesto CL65 3 0.0000 1.00 . . 2192 2.0 0.0419 63 Lincoln Omaha 2 0.0000 1.00 . . 1452 . 0.0487 62 Cincinnati Indianapolis 2 0.0000 1.00 . . 1140 . 0.0507 61 Akron Pittsburgh 2 0.0000 1.00 . . 913 . 0.0582 60 Johnstown Syracuse 2 0.0001 1.00 . . 776 . 0.0611 59 Fort Wayne Toledo 2 0.0001 1.00 . . 650 . 0.0712 58 Houston Lafayette 2 0.0001 1.00 . . 567 . 0.0739 57 Jersey City CL69 3 0.0001 1.00 . . 476 . 0.0775

18:24 Saturday, November 21, 2009 77 Clustering based on Monthly Average Temperatures

Page 38: R Code for Calculating Beale’s F-Type Statistic: c1

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

56 ColumbusGA Jackson 2 0.0001 .999 . . 440 . 0.0791 55 CL61 Cleveland 3 0.0001 .999 . . 400 2.4 0.083 54 Baton Rouge Lake Charles 2 0.0001 .999 . . 379 . 0.0833 53 CL62 ColumbusOH 3 0.0001 .999 . . 347 3.9 0.0906 52 Evansville Lexington 2 0.0001 .999 . . 329 . 0.0944 51 Kansas CityMO Kansas CityKS 2 0.0001 .999 . . 316 . 0.0957 50 Corpus Christi CL66 3 0.0002 .999 . . 291 . 0.1014 49 Little Rock Memphis 2 0.0001 .998 . . 282 . 0.1017 48 CL57 Philadelphia 4 0.0002 .998 . . 266 3.6 0.1041 47 Atlanta Huntsville 2 0.0002 .998 . . 260 . 0.1045 46 Austin San Antonio 2 0.0002 .998 . . 256 . 0.106 45 Chicago CL59 3 0.0002 .998 . . 249 2.7 0.1079 44 Charlotte Knoxville 2 0.0002 .998 . . 246 . 0.1092 43 Buffalo CL60 3 0.0002 .997 . . 240 4.0 0.1096 42 CL56 Shreveport 3 0.0002 .997 . . 236 2.4 0.1138 41 Colorado Springs Denver 2 0.0002 .997 . . 233 . 0.1215 40 CL53 Dayton 4 0.0003 .997 . . 226 3.1 0.124 39 CL43 Worcester 4 0.0003 .996 . . 221 2.1 0.1274 38 Bakersfield Fresno 2 0.0002 .996 . . 220 . 0.129 37 CL55 CL45 6 0.0006 .995 . . 202 5.5 0.1379 36 CL54 CL58 4 0.0005 .995 . . 193 5.3 0.1402

18:24 Saturday, November 21, 2009 78 Clustering based on Monthly Average Temperatures

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

35 Louisville St. Louis 2 0.0003 .995 . . 192 . 0.1522 34 CL39 Grand Rapids 5 0.0005 .994 . . 187 2.4 0.1557

Page 39: R Code for Calculating Beale’s F-Type Statistic: c1

33 CL64 San Bernardino 4 0.0006 .994 . . 181 26.0 0.1628 32 Arlington CL35 3 0.0004 .993 . . 180 1.2 0.1651 31 CL42 CL49 5 0.0008 .992 . . 171 5.1 0.1697 30 CL50 Miami 4 0.0006 .992 . . 168 5.8 0.1703 29 Washington CL51 3 0.0006 .991 . . 167 4.3 0.1786 28 CL29 CL48 7 0.0013 .990 . . 154 6.3 0.1923 27 CL40 CL52 6 0.0012 .989 . . 146 8.0 0.1932 26 CL46 CL36 6 0.0011 .988 . . 141 5.6 0.1952 25 CL47 Nashville 3 0.0007 .987 . . 141 4.7 0.2029 24 CL27 CL28 13 0.0032 .984 . . 120 8.6 0.2374 23 CL37 CL34 11 0.0034 .980 . . 106 15.1 0.2378 22 CL23 Boston 12 0.0011 .979 . . 107 2.0 0.2436 21 CL26 CL30 10 0.0034 .976 . . 98.2 10.0 0.2596 20 CL25 Oklahoma City 4 0.0013 .974 . . 100 2.9 0.2649 19 CL32 Wichita 4 0.0014 .973 . . 102 3.8 0.273 18 CL31 El Paso 6 0.0018 .971 . . 103 5.8 0.2896 17 CL19 CL44 6 0.0024 .969 . . 103 4.1 0.2906 16 CL24 CL63 15 0.0036 .965 . . 99.5 6.3 0.3031 15 CL68 Tacoma 3 0.0021 .963 . . 102 . 0.3328

18:24 Saturday, November 21, 2009 79 Clustering based on Monthly Average Temperatures

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

14 CL18 Riverside 7 0.0026 .960 .949 2.19 104 4.3 0.3515 13 CL17 CL20 10 0.0056 .955 .945 1.67 100 6.4 0.3564 12 CL13 CL38 12 0.0046 .950 .941 1.50 100 3.6 0.378 11 CL21 Dallas/Fort Worth 11 0.0033 .947 .936 1.66 105 4.9 0.3846 10 CL67 CL33 6 0.0063 .940 .930 1.45 105 41.7 0.4115 9 CL11 CL14 18 0.0186 .922 .923 -.16 89.9 19.6 0.4564 8 CL22 CL16 27 0.0336 .888 .915 -2.5 70.4 47.6 0.4669 7 Las Vegas Phoenix 2 0.0033 .885 .904 -1.7 80.8 . 0.4773 6 CL8 CL10 33 0.0273 .858 .890 -2.5 77.1 14.6 0.5451

Page 40: R Code for Calculating Beale’s F-Type Statistic: c1

5 CL6 CL12 45 0.0844 .773 .870 -5.5 55.4 35.3 0.6857 4 CL9 CL7 20 0.0205 .753 .842 -4.6 67.0 9.9 0.7172 3 CL41 CL15 5 0.0170 .736 .794 -1.9 93.3 21.7 0.7192 2 CL5 CL3 50 0.1286 .607 .667 -1.6 105 29.9 1.1237 1 CL2 CL4 70 0.6072 .000 .000 0.00 . 105 1.3406

18:24 Saturday, November 21, 2009 80 Clustering based on Monthly Average Temperatures

Plot of _CCC_*_NCL_. Symbol is value of _NCL_.

‚ ‚ 3 ˆ ‚ ‚ ‚ 1 2 ˆ C ‚ 1 1 u ‚ 1 1 b ‚ i 1 ˆ c ‚ ‚ C ‚ l 0 ˆ 1 u ‚ 9 s ‚ t ‚ e -1 ˆ r ‚ i ‚ 2 n ‚ 7 g -2 ˆ 3 ‚ C ‚ 6 8 r ‚ i -3 ˆ t ‚ e ‚ r ‚ i -4 ˆ o ‚ n ‚ 4 ‚ -5 ˆ ‚ ‚ 5 ‚ -6 ˆ ‚ Šƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒ 0 10 20 30 40 50 60 70

Number of Clusters

NOTE: 125 obs had missing values.

18:24 Saturday, November 21, 2009 81 Clustering based on Monthly Average Temperatures 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Page 41: R Code for Calculating Beale’s F-Type Statistic: c1

Initial Seeds

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 61.53333333 68.32258065 75.90000000 82.41935484 84.96774194 71.36666667 2 58.51666667 64.82258065 71.73333333 74.33870968 74.90322581 73.41666667 3 61.20000000 75.58064516 85.46666667 88.41935484 88.19354839 81.93333333 4 69.63333333 72.19354839 80.03333333 83.12903226 86.12903226 75.50000000 5 66.13333333 80.03225806 89.13333333 91.45161290 93.22580645 87.63333333 6 78.00000000 78.83870968 81.06666667 84.16129032 83.80645161 82.10000000 7 58.81666667 63.38709677 65.66666667 71.51612903 70.09677419 68.60000000 8 49.06666667 61.22580645 69.56666667 74.90322581 68.00000000 62.96666667 9 54.80000000 55.67741935 59.83333333 62.19354839 64.09677419 63.86666667 10 42.53333333 53.48387097 63.03333333 71.32258065 69.03225806 57.90000000 11 53.08888889 62.62365591 73.07777778 80.87096774 75.84946237 69.56666667

Criterion Based on Final Seeds = 1.5757

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 10 2.0489 6.0740 2 9.0021 2 5 1.6267 6.2134 1 9.0021 3 2 2.4135 4.1804 4 9.6229 4 9 1.9133 7.2480 6 8.5285 5 1 . 0 3 14.0939 6 8 1.3488 4.5910 4 8.5285 7 2 0 0 2 10.9251 8 12 1.3755 4.3986 11 10.1381 9 3 1.8350 5.1901 10 16.3540 10 2 0.8203 1.4208 8 14.0807 11 16 1.6956 6.6970 2 9.1851

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ TempApril 8.63420 2.21434 0.943760 16.780915 TempMay 6.63611 1.27664 0.968354 30.599945 TempJune 6.05594 1.18205 0.967423 29.696715 TempJuly 5.36010 1.49190 0.933757 14.096017 TempAug 6.95429 1.99991 0.929284 13.141115

18:24 Saturday, November 21, 2009 82 Clustering based on Monthly Average Temperatures 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ TempSep 6.41754 1.69823 0.940123 15.700985 OVER-ALL 6.75203 1.68522 0.946735 17.773921

Pseudo F Statistic = 104.87

Approximate Expected Over-All R-Squared = 0.68370

Page 42: R Code for Calculating Beale’s F-Type Statistic: c1

Cubic Clustering Criterion = 40.670

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 61.29333333 67.76774194 75.58000000 81.32258065 79.92903226 72.01333333 2 58.48422222 65.41397850 71.93466667 75.80795699 75.44688172 73.96733333 3 62.08571429 74.59216590 82.29523810 86.92857143 86.42857143 81.36904762 4 68.48148148 72.94086022 80.05000000 83.06093190 84.98745520 76.18333333 5 66.13333333 80.03225806 89.13333333 91.45161290 93.22580645 87.63333333 6 74.01250000 77.55241936 81.82500000 83.38709677 85.49596774 80.35000000 7 58.81666667 63.38709677 65.66666667 71.51612903 70.09677419 68.60000000 8 49.40740741 60.90501792 70.10648148 76.12455197 69.37544803 64.75648148 9 52.78888889 54.48387096 59.33333333 62.35483871 64.40860215 62.92222222 10 42.56250000 53.90725807 63.22500000 72.24731183 69.83870968 58.44444445 11 54.26666667 63.86525538 72.92465278 80.45430107 75.38340054 67.51701389

18:24 Saturday, November 21, 2009 83 Clustering based on Monthly Average Temperatures 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Cluster Standard Deviations

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 2.913646055 1.099806057 0.968924567 1.806259591 2.311342787 2.438133265 2 0.478633858 1.210382109 1.119676539 2.745233058 1.419320950 1.838046734 3 1.252589154 1.397920776 4.485077303 2.108286117 2.496054354 0.798020511 4 2.826897647 1.568522471 1.074192203 1.507671542 2.452604555 1.438797725 5 . . . . . . 6 2.041392110 1.003848326 0.597813477 0.535356156 1.738513236 1.440238076 7 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 8 1.987346806 1.372243351 0.912962620 1.547813096 1.029836464 1.109235370 9 3.483346622 2.067286447 0.866025404 0.279363029 0.540101864 1.635825767 10 0.041247900 0.598759772 0.271057604 1.307767376 1.140494811 0.769960718 11 1.818220537 1.186113737 1.326198455 1.124188277 2.460072118 1.860887736

18:24 Saturday, November 21, 2009 84 Clustering based on Monthly Average Temperatures 11 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 1042.78 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 85 Clustering based on Monthly Average Temperatures 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=7 Maxiter=1

Page 43: R Code for Calculating Beale’s F-Type Statistic: c1

Initial Seeds

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 54.80000000 55.67741935 59.83333333 62.19354839 64.09677419 63.86666667 2 56.20000000 65.45161290 73.30000000 82.51612903 81.48387097 67.23333333 3 62.97142857 73.60368664 79.12380952 85.43778802 84.66359447 80.80476190 4 78.00000000 78.83870968 81.06666667 84.16129032 83.80645161 82.10000000 5 58.81666667 63.38709677 65.66666667 71.51612903 70.09677419 68.60000000 6 42.53333333 53.48387097 63.03333333 71.32258065 69.03225806 57.90000000 7 66.13333333 80.03225806 89.13333333 91.45161290 93.22580645 87.63333333

Criterion Based on Final Seeds = 2.2976

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 3 1.8350 5.1901 6 16.9724 2 24 2.3985 9.8498 5 10.1841 3 11 2.1764 8.3718 4 11.4727 4 11 1.7302 8.3212 3 11.4727 5 12 2.3120 8.2913 6 8.8515 6 7 2.5393 7.8255 5 8.8515 7 2 3.2224 11.1628 4 14.6483

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ TempApril 8.63420 2.78129 0.905259 9.555044 TempMay 6.63611 1.92274 0.923351 12.046466 TempJune 6.05594 1.82038 0.917501 11.121329 TempJuly 5.36010 2.29335 0.832857 4.982899 TempAug 6.95429 1.99256 0.925044 12.341137 TempSep 6.41754 2.62731 0.846970 5.534684 OVER-ALL 6.75203 2.26858 0.896930 8.702160

Pseudo F Statistic = 91.37

18:24 Saturday, November 21, 2009 86 Clustering based on Monthly Average Temperatures 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=7 Maxiter=1

Approximate Expected Over-All R-Squared = 0.58008

Cubic Clustering Criterion = 39.048

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 52.78888889 54.48387096 59.33333333 62.35483871 64.40860215 62.92222222 2 56.73606482 65.16173835 73.49912037 79.77585125 76.49923835 70.17861111 3 65.65952381 71.00795978 78.23549784 82.47821533 83.22748220 74.88679654 4 73.15000000 76.74340176 81.62878788 83.41495601 85.96041056 79.65757576

Page 44: R Code for Calculating Beale’s F-Type Statistic: c1

5 52.47962963 62.04569892 69.98240741 76.88799283 70.68548387 65.55462963 6 46.04960317 58.40514593 67.60396826 74.07680492 69.03993855 62.81904762 7 63.66666667 77.80645161 87.30000000 89.93548387 90.70967742 84.78333333

Cluster Standard Deviations

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 3.483346622 2.067286447 0.866025404 0.279363029 0.540101864 1.635825767 2 2.668725412 1.621903295 1.547236310 2.729201535 2.271558855 3.124588994 3 2.778721179 2.091273831 1.828891790 1.718547848 1.995731202 2.458299229 4 2.467668717 1.645010344 0.720034372 1.099193038 2.034859621 1.816289924 5 3.163535874 1.423777322 2.167531337 2.999754590 1.712476269 1.845876640 6 2.546336244 3.184729020 3.032364374 1.564019412 0.885878696 3.104395624 7 3.488393451 3.147765669 2.592724860 2.144130237 3.558343799 4.030508653

18:24 Saturday, November 21, 2009 87 Clustering based on Monthly Average Temperatures 7 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 2217.25 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 88 Plot of first 2 PCs: Clustered by Temp

Plot of PCT1*PCT2. Symbol is value of CLUSTER.

PCT1 ‚ ‚ 40 ˆ ‚ ‚ ‚ ‚ 1 30 ˆ ‚ ‚ 4 ‚ 4 4 ‚ 4 44 4 20 ˆ 4 1 ‚ 4 ‚ 7 7 7 ‚ 7 7 7 ‚ 7 10 ˆ ‚ 88 8 ‚ 8 ‚ 8 8 ‚ 8 8 8 8 0 ˆ 8 8 ‚ 5 1 1 ‚ 5 5 1 11 ‚ 11 1 1 1 ‚ 1 1 -10 ˆ 3 1 1 ‚ 6 6 ‚ 66 6 6 6 ‚ 6 ‚ 66 6 -20 ˆ 6

Page 45: R Code for Calculating Beale’s F-Type Statistic: c1

‚ ‚ ‚ 2 9 ‚ 9 -30 ˆ ‚ 2 ‚ ‚ ‚ -40 ˆ ‚ Šƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒ -15 -10 -5 0 5 10

PCT2

NOTE: 6 obs hidden.

18:24 Saturday, November 21, 2009 89 Cities in their Clusters

Temp Temp TempObs city April TempMay June July TempAug TempSep CLUSTER CLUSNAME

1 Cincinnati 55.3000 63.7742 73.2667 79.1935 72.9677 67.0667 1 CL16 2 ColumbusOH 55.1667 65.0323 74.7333 80.3548 73.3226 68.1000 1 CL16 3 Dayton 53.8333 63.8065 72.7333 78.6452 71.5806 67.0000 1 CL16 4 Evansville 58.0000 65.6452 74.7667 79.6452 74.6129 68.5000 1 CL16 5 Indianapolis 55.2667 64.5484 74.0000 79.5161 72.6129 67.2667 1 CL16 6 Jersey City 53.5667 63.5484 74.3667 81.0968 76.5484 69.5333 1 CL16 7 Kansas CityKS 53.6667 64.3387 72.6167 82.0000 77.8871 65.8167 1 CL16 8 Kansas CityMO 54.8000 63.6452 71.7667 81.1613 76.5484 65.9667 1 CL16 9 Kingston 53.0889 62.6237 73.0778 80.8710 75.8495 69.5667 1 CL16 10 Lexington 56.7000 65.5161 73.6667 79.8065 75.9355 68.9333 1 CL16 11 Lincoln 51.0667 61.8710 70.4000 80.8387 74.1935 64.1333 1 CL16 12 New York 53.0889 62.6237 73.0778 80.8710 75.8495 69.5667 1 CL16 13 Omaha 51.5556 62.2581 70.8222 80.6882 73.3548 64.0889 1 CL16 14 Philadelphia 53.8000 64.1613 73.1000 81.3871 77.7097 70.1667 1 CL16 15 Washington 53.1667 63.0000 71.1000 78.6774 75.6774 67.3333 1 CL16 16 Oakland 54.8000 55.6774 59.8333 62.1935 64.0968 63.8667 2 CL15 17 San Jose 54.8000 55.6774 59.8333 62.1935 64.0968 63.8667 2 CL15 18 Tacoma 48.7667 52.0968 58.3333 62.6774 65.0323 61.0333 2 CL15 19 Los Angeles 58.8167 63.3871 65.6667 71.5161 70.0968 68.6000 3 CL67 20 Santa Ana/Anaheim 58.8167 63.3871 65.6667 71.5161 70.0968 68.6000 3 CL67 21 Austin 72.0000 76.6452 81.9667 83.4516 88.5161 81.6667 4 CL11 22 Baton Rouge 72.0333 74.7419 80.5000 81.8710 85.2903 76.3000 4 CL11 23 Corpus Christi 74.9000 78.8387 82.9667 82.9355 84.3871 79.8000 4 CL11 24 Dallas/Fort Worth 68.2833 73.8871 82.1167 86.0484 90.2097 79.2667 4 CL11 25 Houston 73.1667 76.7742 82.1667 83.3226 87.0968 78.1667 4 CL11 26 Lafayette 73.4000 76.9032 81.5667 82.5161 85.7419 78.4333 4 CL11 27 Lake Charles 72.2333 75.1290 80.7000 82.5484 86.0968 77.8667 4 CL11 28 Miami 78.0000 78.8387 81.0667 84.1613 83.8065 82.1000 4 CL11 29 San Antonio 71.4333 76.3548 82.0667 83.0968 86.4194 80.5667 4 CL11 30 St. Petersburg 74.6000 78.0323 81.4000 83.8065 84.0000 81.0333 4 CL11 31 Tampa 74.6000 78.0323 81.4000 83.8065 84.0000 81.0333 4 CL11 32 Modesto 58.5167 64.8226 71.7333 74.3387 74.9032 73.4167 5 CL33 33 Sacramento 58.3267 64.2581 71.2067 73.6258 74.4387 73.2867 5 CL33 34 San Bernardino 59.2889 66.7957 71.2667 76.7312 75.5054 72.8778 5 CL33 35 Stockton 58.2222 64.5484 71.5667 74.1183 74.5161 73.0222 5 CL33 36 Akron 51.4000 61.6129 70.0667 76.0968 68.4516 63.7333 6 CL22 37 Boston 49.4000 58.4194 71.2000 76.0323 71.6452 67.3667 6 CL22 38 Buffalo 46.1333 59.8387 68.5667 74.5806 68.0645 64.4667 6 CL22 39 Chicago 49.8000 61.8710 70.5667 78.5806 70.5484 63.6667 6 CL22 40 Cleveland 50.5667 61.2581 70.4000 76.4194 69.3548 65.1667 6 CL22 41 Fort Wayne 51.5000 62.5806 71.6333 78.6129 69.7419 64.5667 6 CL22 42 Grand Rapids 49.0667 61.2258 69.5667 74.9032 68.0000 62.9667 6 CL22 43 Johnstown 47.8000 60.3226 69.7667 76.0000 69.0968 64.9333 6 CL22 44 Pittsburgh 52.1000 61.2581 69.6000 76.2581 69.1935 64.4000 6 CL22 45 Syracuse 46.8333 60.9032 69.9667 75.1613 69.0968 65.1000 6 CL22

Page 46: R Code for Calculating Beale’s F-Type Statistic: c1

46 Toledo 50.9000 62.8387 71.0333 77.4516 69.9677 65.3333 6 CL22 47 Worcester 47.3889 58.7312 68.9111 73.3978 69.3441 65.3778 6 CL22 48 ColumbusGA 68.2667 71.8548 78.3667 82.0323 84.3387 75.0833 7 CL14 49 El Paso 63.4333 74.3548 80.2333 81.3226 81.4839 75.6667 7 CL14

18:24 Saturday, November 21, 2009 90 Cities in their Clusters

Temp Temp TempObs city April TempMay June July TempAug TempSep CLUSTER CLUSNAME

50 Jackson 69.5000 71.7742 79.7000 82.1935 84.2258 75.3667 7 CL14 51 Little Rock 65.6833 71.1129 78.9000 84.4677 84.2097 75.1667 7 CL14 52 Memphis 67.2667 71.4194 79.9000 83.9355 82.9032 75.4333 7 CL14 53 Riverside 62.9714 73.6037 79.1238 85.4378 84.6636 80.8048 7 CL14 54 Shreveport 69.6333 72.1935 80.0333 83.1290 86.1290 75.5000 7 CL14 55 Arlington 56.7667 67.4839 74.9333 83.2258 79.9032 70.2667 8 CL12 56 Atlanta 65.3667 69.1290 75.1667 79.3871 82.1290 73.3000 8 CL12 57 Bakersfield 58.0667 66.6452 73.9000 80.2258 77.8710 77.2333 8 CL12 58 Charlotte 62.2333 65.9677 73.6333 79.0645 79.6774 69.3667 8 CL12 59 Fresno 58.7333 68.2258 76.2000 80.7097 78.6452 77.4333 8 CL12 60 Huntsville 65.7667 69.4194 76.4667 80.7419 80.8387 74.0333 8 CL12 61 Knoxville 61.4000 66.3871 75.1333 78.8387 78.0000 70.1000 8 CL12 62 Louisville 59.5000 67.8065 76.5000 83.4839 78.7742 72.2667 8 CL12 63 Nashville 62.8333 67.9032 76.8000 82.1935 79.6129 72.0333 8 CL12 64 Oklahoma City 61.5333 68.3226 75.9000 82.4194 84.9677 71.3667 8 CL12 65 St. Louis 58.8000 67.0323 75.0667 83.1613 76.7419 69.9667 8 CL12 66 Wichita 56.2000 65.4516 73.3000 82.5161 81.4839 67.2333 8 CL12 67 Colorado Springs 42.5333 53.4839 63.0333 71.3226 69.0323 57.9000 9 CL41 68 Denver 42.5917 54.3306 63.4167 73.1720 70.6452 58.9889 9 CL41 69 Las Vegas 61.2000 75.5806 85.4667 88.4194 88.1935 81.9333 10 Las Vegas 70 Phoenix 66.1333 80.0323 89.1333 91.4516 93.2258 87.6333 11 Phoenix

18:24 Saturday, November 21, 2009 91 Clustering based on Monthly Average Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Eigenvalues of the Covariance Matrix

Eigenvalue Difference Proportion Cumulative

1 91.4204695 34.1181979 0.4525 0.4525 2 57.3022716 27.7307075 0.2836 0.7361 3 29.5715640 17.1594150 0.1464 0.8824 4 12.4121490 4.6460029 0.0614 0.9438 5 7.7661461 4.1857120 0.0384 0.9823 6 3.5804341 0.0177 1.0000

Root-Mean-Square Total-Sample Standard Deviation = 5.80306 Root-Mean-Square Distance Between Observations = 20.10239

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

69 St. Petersburg Tampa 2 0.0001 1.00 . . 242 . 0.0648 68 Cleveland Dayton 2 0.0001 1.00 . . 190 . 0.0815 67 Oakland San Jose 2 0.0002 1.00 . . 136 . 0.1109 66 Akron CL68 3 0.0004 .999 . . 78.8 4.6 0.1572

Page 47: R Code for Calculating Beale’s F-Type Statistic: c1

65 Sacramento Stockton 2 0.0004 .999 . . 65.0 . 0.1703 64 Riverside San Bernardino 2 0.0005 .998 . . 56.8 . 0.1804 63 Denver Phoenix 2 0.0005 .998 . . 50.7 . 0.1945 62 Atlanta Memphis 2 0.0006 .997 . . 46.9 . 0.1976 61 Kansas CityMO St. Louis 2 0.0006 .997 . . 44.3 . 0.201 60 CL67 Tacoma 3 0.0008 .996 . . 40.3 4.6 0.2134 59 Buffalo Syracuse 2 0.0007 .995 . . 38.2 . 0.2263 58 Fort Wayne Indianapolis 2 0.0008 .994 . . 36.3 . 0.2405 57 CL61 Louisville 3 0.0009 .993 . . 34.4 1.6 0.2412

18:24 Saturday, November 21, 2009 92 Clustering based on Monthly Average Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

56 El Paso Los Angeles 2 0.0009 .992 . . 33.1 . 0.253 55 Bakersfield Fresno 2 0.0009 .991 . . 32.1 . 0.2559 54 CL63 Kansas CityKS 3 0.0012 .990 . . 30.6 2.2 0.267 53 Little Rock Shreveport 2 0.0011 .989 . . 29.8 . 0.271 52 CL66 Toledo 4 0.0017 .987 . . 27.9 6.1 0.2878 51 Houston Lafayette 2 0.0012 .986 . . 27.3 . 0.2926 50 Oklahoma City Wichita 2 0.0013 .985 . . 26.7 . 0.2985 49 ColumbusGA Jackson 2 0.0014 .984 . . 26.2 . 0.3125 48 CL52 Cincinnati 5 0.0019 .982 . . 25.1 2.5 0.3153 47 Modesto CL65 3 0.0018 .980 . . 24.4 4.2 0.3158 46 CL59 Pittsburgh 3 0.0017 .978 . . 23.9 2.3 0.3196 45 CL56 Santa Ana/Anaheim 3 0.0017 .976 . . 23.6 1.8 0.3211 44 Boston Worcester 2 0.0015 .975 . . 23.5 . 0.3262 43 Evansville Lexington 2 0.0016 .973 . . 23.5 . 0.3302 42 Colorado Springs Kingston 2 0.0017 .972 . . 23.5 . 0.3386 41 CL60 CL69 5 0.0036 .968 . . 22.0 10.2 0.3407 40 Jersey City Philadelphia 2 0.0018 .966 . . 22.0 . 0.3544 39 CL51 San Antonio 3 0.0022 .964 . . 21.9 1.7 0.3652 38 Arlington New York 2 0.0020 .962 . . 22.0 . 0.3681

Page 48: R Code for Calculating Beale’s F-Type Statistic: c1

37 Chicago Johnstown 2 0.0020 .960 . . 22.1 . 0.3757 36 CL48 CL58 7 0.0041 .956 . . 21.1 4.2 0.3763

18:24 Saturday, November 21, 2009 93 Clustering based on Monthly Average Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

35 Las Vegas CL64 3 0.0027 .953 . . 21.0 5.6 0.382 34 Huntsville Nashville 2 0.0022 .951 . . 21.2 . 0.3899 33 Dallas/Fort Worth CL53 3 0.0027 .948 . . 21.3 2.5 0.3965 32 CL62 CL49 4 0.0036 .945 . . 21.0 3.7 0.3988 31 CL57 Knoxville 4 0.0033 .942 . . 20.9 4.3 0.4097 30 Austin Lake Charles 2 0.0025 .939 . . 21.3 . 0.4143 29 CL54 CL45 6 0.0053 .934 . . 20.7 4.9 0.4144 28 CL44 CL42 4 0.0036 .930 . . 20.7 2.2 0.4223 27 Lincoln CL41 6 0.0039 .926 . . 20.8 3.4 0.4422 26 CL36 CL37 9 0.0057 .921 . . 20.4 3.6 0.4548 25 CL40 Washington 3 0.0034 .917 . . 20.8 1.9 0.4551 24 CL43 CL31 6 0.0054 .912 . . 20.7 3.4 0.4553 23 CL30 CL39 5 0.0047 .907 . . 20.9 2.4 0.4655 22 CL29 CL47 9 0.0079 .899 . . 20.4 4.7 0.4665 21 CL26 Grand Rapids 10 0.0043 .895 . . 20.9 2.0 0.4781 20 CL33 CL50 5 0.0071 .888 . . 20.8 4.2 0.519 19 CL21 ColumbusOH 11 0.0053 .883 . . 21.3 2.2 0.5219 18 CL20 CL34 7 0.0070 .876 . . 21.5 2.4 0.5384 17 CL22 CL35 12 0.0127 .863 . . 20.8 5.6 0.5543 16 Charlotte CL24 7 0.0065 .856 . . 21.5 2.8 0.573 15 Corpus Christi Miami 2 0.0048 .852 . . 22.5 . 0.5748

18:24 Saturday, November 21, 2009 94 Clustering based on Monthly Average Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T

Page 49: R Code for Calculating Beale’s F-Type Statistic: c1

RMS i CCC PSF PST2 Dist e

14 CL38 CL46 5 0.0109 .841 .833 0.70 22.7 7.4 0.6126 13 CL19 CL14 16 0.0222 .818 .822 -.27 21.4 7.5 0.6411 12 CL32 CL16 11 0.0209 .798 .809 -.93 20.8 7.9 0.6494 11 CL23 Baton Rouge 6 0.0088 .789 .796 -.53 22.0 3.3 0.66 10 CL28 CL27 10 0.0253 .763 .781 -1.2 21.5 13.2 0.6872 9 CL12 Omaha 12 0.0099 .754 .763 -.56 23.3 2.2 0.7162 8 CL18 CL17 19 0.0558 .698 .743 -2.4 20.4 16.7 0.802 7 CL11 CL15 8 0.0228 .675 .719 -2.2 21.8 5.7 0.8471 6 CL13 CL9 28 0.0950 .580 .689 -4.8 17.7 20.8 0.8789 5 CL55 CL25 5 0.0246 .555 .651 -4.2 20.3 12.0 0.8849 4 CL6 CL10 38 0.0854 .470 .600 -5.3 19.5 12.1 0.8964 3 CL5 CL8 24 0.0475 .422 .522 -3.4 24.5 7.3 0.9117 2 CL4 CL3 62 0.2127 .210 .354 -4.1 18.0 24.0 1.0401 1 CL2 CL7 70 0.2097 .000 .000 0.00 . 18.0 1.2794

18:24 Saturday, November 21, 2009 95 Clustering based on Monthly Average Ozone

Plot of _CCC_*_NCL_. Symbol is value of _NCL_.

‚ 1 ˆ ‚ ‚ 1 ‚ ‚ ‚ 0 ˆ 1 ‚ C ‚ 1 u ‚ 9 1 b ‚ i ‚ c -1 ˆ 1 ‚ 1 C ‚ l ‚ u ‚ s ‚ t -2 ˆ e ‚ 7 r ‚ 8 i ‚ n ‚ g ‚ -3 ˆ C ‚ r ‚ i ‚ 3 t ‚ e ‚ r -4 ˆ

Page 50: R Code for Calculating Beale’s F-Type Statistic: c1

i ‚ 2 5 o ‚ n ‚ ‚ ‚ 6 -5 ˆ ‚ ‚ 4 ‚ ‚ ‚ -6 ˆ Šƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒ 0 10 20 30 40 50 60 70

Number of Clusters

NOTE: 125 obs had missing values.

18:24 Saturday, November 21, 2009 96 Clustering based on Monthly Average Ozone 3 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=3 Maxiter=1

Initial Seeds

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -3.30958634 3.98311820 8.52224439 7.12891093 -6.89333214 -9.57197828 2 8.26810673 2.13984674 -5.59714122 -11.35809613 9.27459675 11.64296533 3 4.01150951 12.98353884 14.80178876 16.41516523 9.86961223 13.51574845

Criterion Based on Final Seeds = 4.1148

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 30 3.9221 13.4133 3 14.6635 2 18 4.7236 18.9730 1 17.7182 3 22 4.1250 14.1240 1 14.6635

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ O3April 4.87097 4.10453 0.310519 0.450366 O3May 3.80274 2.50816 0.577582 1.367326 O3June 5.97917 3.74635 0.618793 1.623244 O3July 7.59798 4.60614 0.643135 1.802182 O3Aug 6.53520 5.64898 0.274483 0.378328 O3Sep 5.26091 3.95173 0.452128 0.825245 OVER-ALL 5.80306 4.20153 0.490991 0.964602

Pseudo F Statistic = 32.31

Approximate Expected Over-All R-Squared = 0.36687

Cubic Clustering Criterion = 6.061

Page 51: R Code for Calculating Beale’s F-Type Statistic: c1

WARNING: The two values above are invalid for correlated variables.

18:24 Saturday, November 21, 2009 97 Clustering based on Monthly Average Ozone 3 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=3 Maxiter=1

Cluster Means

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -0.20307758 4.07192245 5.82244924 6.77264454 1.17191651 -2.95667761 2 4.52865729 5.80365272 -2.57800579 -5.11282431 5.92576272 4.39970909 3 5.69458179 10.71848511 9.64068091 10.34498617 9.01809097 3.91036012

Cluster Standard Deviations

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.994072144 2.452057404 3.807017439 3.966595612 4.553170323 3.222263526 2 4.204102492 2.707159103 3.032091341 4.789332229 7.868298195 3.850926801 3 2.236205285 2.415563775 4.161942614 5.233977516 4.802547642 4.845580928

18:24 Saturday, November 21, 2009 98 Clustering based on Monthly Average Ozone 3 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 7111.38 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 99 Clustering based on Monthly Average Ozone 5 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=5 Maxiter=1

Initial Seeds

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -3.30958634 3.98311820 8.52224439 7.12891093 -6.89333214 -9.57197828 2 -2.24268385 3.42536915 0.23333572 -1.43411370 11.69564504 1.00111745 3 8.86449487 15.79199284 15.30057713 5.32796804 5.59274612 -0.30986960 4 7.48432721 7.78439194 -8.50971825 -12.29273944 -8.16825369 -2.35173186 5 2.01369361 10.12843346 14.03764848 13.96454628 9.53565765 16.27516873

Criterion Based on Final Seeds = 3.6648

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 21 3.3848 12.2849 3 13.6787

Page 52: R Code for Calculating Beale’s F-Type Statistic: c1

2 18 4.4022 17.2345 4 15.7258 3 16 3.3962 13.9199 5 11.3517 4 11 3.7464 11.7913 2 15.7258 5 4 3.8702 12.1822 3 11.3517

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ O3April 4.87097 3.50504 0.512225 1.050124 O3May 3.80274 2.66327 0.537938 1.164213 O3June 5.97917 3.26968 0.718296 2.549819 O3July 7.59798 4.75557 0.630961 1.709739 O3Aug 6.53520 4.22203 0.606822 1.543377 O3Sep 5.26091 3.75839 0.519221 1.079956 OVER-ALL 5.80306 3.75579 0.605405 1.534242

Pseudo F Statistic = 24.93

Approximate Expected Over-All R-Squared = 0.51809

18:24 Saturday, November 21, 2009 100 Clustering based on Monthly Average Ozone 5 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=5 Maxiter=1

Cubic Clustering Criterion = 5.195

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -1.37261200 3.66326749 7.32669792 8.37155670 0.52532044 -3.91449985 2 1.64288672 5.60831177 0.69776353 0.08985295 11.20782635 3.92822043 3 6.46443827 10.64547646 9.91652553 9.51041115 6.76657723 1.56084536 4 7.37065246 6.40253442 -3.10617794 -4.84578661 -1.90386415 2.16274421 5 3.86225122 10.94909096 12.36187552 15.61380618 10.03097306 9.81379379

Cluster Standard Deviations

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.436830395 2.204788517 3.346896460 3.486642350 3.757750292 2.591409946 2 4.047557712 3.525714219 3.169695819 5.301443896 5.382104031 4.510351631 3 2.149778708 2.792820385 3.462461526 4.995105759 3.198001249 3.100799417 4 1.992242725 1.730462649 3.115685245 5.848870468 4.021864110 4.142337911 5 2.402521820 1.361128457 2.778883533 3.302557782 4.783516207 6.382205181

18:24 Saturday, November 21, 2009 101 Clustering based on Monthly Average Ozone 5 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 5640.93

Page 53: R Code for Calculating Beale’s F-Type Statistic: c1

ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 102 Clustering based on Monthly Average Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=7 Maxiter=1

Initial Seeds

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.06688135 5.12388166 11.97256249 21.14757640 9.28659646 -2.58668876 2 -3.30958634 3.98311820 8.52224439 7.12891093 -6.89333214 -9.57197828 3 5.96883894 11.14634118 2.94742139 6.26571927 20.34200926 5.51697099 4 8.86449487 15.79199284 15.30057713 5.32796804 5.59274612 -0.30986960 5 2.01369361 10.12843346 14.03764848 13.96454628 9.53565765 16.27516873 6 -0.40624116 0.81119803 -0.80711924 4.54770896 -1.08807176 6.44134763 7 7.48432721 7.78439194 -8.50971825 -12.29273944 -8.16825369 -2.35173186

Criterion Based on Final Seeds = 3.4034

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 8 3.6501 12.0363 4 12.3583 2 14 2.9824 11.5876 6 12.6695 3 8 3.5398 13.3005 6 13.1548 4 13 2.7978 9.8745 1 12.3583 5 3 3.0132 7.9883 4 12.9437 6 16 3.9889 11.7918 2 12.6695 7 8 3.8285 15.7380 6 14.1402

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ O3April 4.87097 3.90818 0.412226 0.701335 O3May 3.80274 2.77176 0.514925 1.061538 O3June 5.97917 2.63120 0.823186 4.655660 O3July 7.59798 3.29188 0.828611 4.834682 O3Aug 6.53520 4.31568 0.601827 1.511472 O3Sep 5.26091 3.47637 0.601322 1.508292 OVER-ALL 5.80306 3.45028 0.677236 2.098240

Pseudo F Statistic = 22.03

18:24 Saturday, November 21, 2009 103 Clustering based on Monthly Average Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=7 Maxiter=1

Approximate Expected Over-All R-Squared = 0.59957

Cubic Clustering Criterion = 5.259

WARNING: The two values above are invalid for correlated variables.

Page 54: R Code for Calculating Beale’s F-Type Statistic: c1

Cluster Means

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 1.25194369 6.27621403 10.64438574 16.43691346 6.75613013 -1.59201189 2 -0.92859996 3.59488084 7.99777370 7.33803545 -1.20594602 -4.65707045 3 2.80439454 6.98237597 2.10474696 2.89753242 15.96437469 4.04872784 4 6.89865845 11.23352997 9.45713320 7.45510164 6.69291103 2.17356838 5 4.41013437 11.17363991 12.47357236 14.20321659 7.97560399 12.42350471 6 1.07504956 5.12323397 0.47084355 0.76563573 3.77020191 0.77926428 7 7.64253012 5.56306129 -5.18681072 -8.80575147 0.51006816 5.50906065

Cluster Standard Deviations

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 3.815392153 3.490876049 2.378852816 3.052768390 5.530930456 2.761349245 2 4.932208160 2.193674268 2.428324794 1.968586953 2.925368817 2.428952433 3 3.250716101 3.252401724 2.567536739 3.426180248 2.910498198 5.218806262 4 1.937112654 2.568467482 3.663109917 2.374145409 2.843290457 3.078799117 5 2.618608595 1.573681236 3.392408206 2.102796675 2.995962130 4.498362815 6 5.135403795 3.194126421 2.025326436 4.326755314 5.269868944 2.881014290 7 1.502757850 1.887672663 2.006388596 4.269784959 6.061095442 4.809473248

18:24 Saturday, November 21, 2009 104 Clustering based on Monthly Average Ozone 7 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 4864.81 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 105 Clustering based on Monthly Average Ozone 9 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=9 Maxiter=1

Initial Seeds

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 8.75283294 8.21885676 -0.00513983 1.68478128 -3.94270346 -1.07305408 2 7.48432721 7.78439194 -8.50971825 -12.29273944 -8.16825369 -2.35173186 3 5.96883894 11.14634118 2.94742139 6.26571927 20.34200926 5.51697099 4 8.26810673 2.13984674 -5.59714122 -11.35809613 9.27459675 11.64296533 5 4.01150951 12.98353884 14.80178876 16.41516523 9.86961223 13.51574845 6 4.48912974 13.43180690 0.16090450 -3.64721296 8.20881388 3.44726784 7 4.06688135 5.12388166 11.97256249 21.14757640 9.28659646 -2.58668876 8 -5.91670883 -1.55883656 9.12688041 8.06928022 -0.38384097 -3.32774353 9 8.86449487 15.79199284 15.30057713 5.32796804 5.59274612 -0.30986960

Criterion Based on Final Seeds = 2.9420

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between

Page 55: R Code for Calculating Beale’s F-Type Statistic: c1

Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 12 3.5213 11.4839 8 13.0045 2 2 3.3359 5.7779 4 14.2735 3 5 2.5549 7.2640 6 12.4498 4 4 2.2664 5.6117 6 12.6695 5 3 3.0132 7.9883 9 12.5150 6 8 2.9851 8.6343 3 12.4498 7 7 3.4787 9.9324 9 11.9530 8 18 3.2438 12.9188 1 13.0045 9 11 2.6511 10.2040 7 11.9530

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ O3April 4.87097 2.70501 0.727362 2.667867 O3May 3.80274 2.60711 0.584468 1.406551 O3June 5.97917 3.37796 0.717832 2.543992 O3July 7.59798 2.95157 0.866590 6.495668 O3Aug 6.53520 3.84097 0.694617 2.274577 O3Sep 5.26091 3.02915 0.706910 2.411918 OVER-ALL 5.80306 3.11355 0.745505 2.929354

18:24 Saturday, November 21, 2009 106 Clustering based on Monthly Average Ozone 9 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=9 Maxiter=1

Pseudo F Statistic = 22.34

Approximate Expected Over-All R-Squared = 0.65542

Cubic Clustering Criterion = 6.644

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 7.09671412 5.80823047 1.95068875 2.91728846 -1.41213621 -0.40667652 2 6.73614450 6.33473816 -6.86289131 -12.66860511 -6.61350101 2.69328726 3 4.14640229 8.84607284 2.59942184 4.06500615 17.62368070 6.76560179 4 7.02342693 4.47806879 -4.48030574 -9.91927649 5.54248032 8.95430358 5 4.41013437 11.17363991 12.47357236 14.20321659 7.97560399 12.42350471 6 1.09874471 5.73519245 -0.37928667 -2.84780007 9.71589421 2.66212463 7 2.25565093 6.69491908 11.20023032 16.86562694 6.55363531 -0.88751870 8 -3.24204291 3.48350440 6.13523080 7.04665691 1.68218503 -3.96840747 9 6.70841642 11.72265832 10.21670856 7.60850509 7.48134490 2.31337570

Cluster Standard Deviations

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 2.986954364 2.700008859 4.743887698 3.799293203 2.646506989 3.773629563 2 1.058090131 2.050120045 2.328964990 0.531554321 2.198752326 7.134734461 3 1.402965098 2.278399434 2.425237216 3.639739580 2.354371490 2.707947965 4 0.870833345 1.884868362 2.227655916 2.455765274 3.277525013 2.184521450 5 2.618608595 1.573681236 3.392408206 2.102796675 2.995962130 4.498362815 6 3.958574969 3.633564959 2.324302830 2.571176241 2.987359060 1.911492449 7 2.753317399 3.546968885 1.928325959 3.026087409 5.941970905 2.064862845

Page 56: R Code for Calculating Beale’s F-Type Statistic: c1

8 2.725690209 1.942719792 3.445345603 2.727510740 4.964051672 2.824853239 9 2.043062526 2.485592110 3.460027213 2.544380846 2.290962059 2.850258697

18:24 Saturday, November 21, 2009 107 Clustering based on Monthly Average Ozone 9 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 3635.23 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 108 Clustering based on Monthly Average Ozone 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Initial Seeds

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -3.30958634 3.98311820 8.52224439 7.12891093 -6.89333214 -9.57197828 2 -8.25527047 1.06793709 2.06343332 2.70012585 2.64255828 -0.43247144 3 5.96883894 11.14634118 2.94742139 6.26571927 20.34200926 5.51697099 4 8.26810673 2.13984674 -5.59714122 -11.35809613 9.27459675 11.64296533 5 2.01369361 10.12843346 14.03764848 13.96454628 9.53565765 16.27516873 6 4.48912974 13.43180690 0.16090450 -3.64721296 8.20881388 3.44726784 7 8.75283294 8.21885676 -0.00513983 1.68478128 -3.94270346 -1.07305408 8 4.06688135 5.12388166 11.97256249 21.14757640 9.28659646 -2.58668876 9 0.53066296 2.74408439 4.20306990 3.62915275 12.72652324 -6.93428130 10 7.48432721 7.78439194 -8.50971825 -12.29273944 -8.16825369 -2.35173186 11 8.86449487 15.79199284 15.30057713 5.32796804 5.59274612 -0.30986960

Criterion Based on Final Seeds = 2.7245

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 11 2.8285 10.0096 2 9.2142 2 8 2.6940 9.9624 1 9.2142 3 5 2.5549 7.2640 9 12.8845 4 4 2.2664 5.6117 6 10.4025 5 4 3.3857 8.5462 11 10.8253 6 5 2.9641 7.5750 9 9.0370 7 8 2.6678 8.0140 2 14.0015 8 8 3.6501 12.0124 11 12.3746 9 4 2.7489 9.7050 6 9.0370 10 2 3.3359 5.7779 4 14.2735 11 11 2.6389 9.7479 5 10.8253

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ O3April 4.87097 3.05149 0.664420 1.979917 O3May 3.80274 2.47022 0.639189 1.771535

Page 57: R Code for Calculating Beale’s F-Type Statistic: c1

O3June 5.97917 2.96705 0.789443 3.749309 O3July 7.59798 2.50061 0.907381 9.796941 O3Aug 6.53520 3.30080 0.781866 3.584334

18:24 Saturday, November 21, 2009 109 Clustering based on Monthly Average Ozone 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ O3Sep 5.26091 2.88092 0.743585 2.899921 OVER-ALL 5.80306 2.87706 0.789822 3.757866

Pseudo F Statistic = 22.17

Approximate Expected Over-All R-Squared = 0.69873

Cubic Clustering Criterion = 8.009

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -1.09268516 3.46514677 8.64175868 8.11577446 -1.01048508 -5.04955317 2 -3.48425008 3.06246315 2.43870700 5.05249131 2.63728193 -0.82443600 3 4.14640229 8.84607284 2.59942184 4.06500615 17.62368070 6.76560179 4 7.02342693 4.47806879 -4.48030574 -9.91927649 5.54248032 8.95430358 5 4.98540518 10.36442721 10.85269907 12.63935970 7.05165975 11.32672332 6 2.72686671 6.85666709 -1.04563577 -4.25233241 8.95112472 3.60972339 7 8.07341687 6.94058169 0.39950800 0.96214565 -2.51325451 -0.75772415 8 1.25194369 6.27621403 10.64438574 16.43691346 6.75613013 -1.59201189 9 -1.07842822 3.58557214 1.59923885 0.52710356 11.42451333 -0.92147529 10 6.73614450 6.33473816 -6.86289131 -12.66860511 -6.61350101 2.69328726 11 6.76679150 11.74399646 10.13768412 7.55794238 7.32469658 2.06903749

18:24 Saturday, November 21, 2009 110 Clustering based on Monthly Average Ozone 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Cluster Standard Deviations

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.469460589 2.302012577 2.228338570 1.290021061 3.110606160 2.533996015 2 3.044371546 1.599552755 1.893820845 1.690314861 3.670540899 3.435289684 3 1.402965098 2.278399434 2.425237216 3.639739580 2.354371490 2.707947965 4 0.870833345 1.884868362 2.227655916 2.455765274 3.277525013 2.184521450 5 2.427993678 2.066466188 4.263942985 3.567972726 3.065705668 4.278071573 6 3.846352978 4.252022685 1.863006008 2.161245966 2.998710843 1.645390578 7 2.202958792 1.635527457 4.439329167 2.928916538 1.965294863 1.739311787 8 3.815392153 3.490876049 2.378852816 3.052768390 5.530930456 2.761349245 9 2.491516828 1.193803886 3.002951501 2.169497532 2.643428349 4.122293824 10 1.058090131 2.050120045 2.328964990 0.531554321 2.198752326 7.134734461

Page 58: R Code for Calculating Beale’s F-Type Statistic: c1

11 2.052303188 2.450602601 3.574254784 2.542489940 2.573278076 2.388372016

18:24 Saturday, November 21, 2009 111 Clustering based on Monthly Average Ozone 11 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 3117.59 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 112 Plot of first 2 PCs: Clustered by Ozone

Plot of PCO1*PCO2. Symbol is value of CLUSTER.

PCO1 ‚ ‚ 20 ˆ ‚ ‚ 9 9 ‚ 15 ˆ 9 ‚ 2 5 ‚ ‚ 2 2 5 10 ˆ 2 2 3 3 ‚ 2 ‚ 2 3 3 ‚ 2 3 3 5 ˆ 2 2 22 ‚ 8 8 6 ‚ 2 2 3 3 6 ‚ 2 4 8 4 3 3 3 6 0 ˆ 2 6 ‚ 8 4 4 ‚ 4 ‚ 4 6 -5 ˆ 1 6 ‚ 1 1 1 4 4 6 ‚ ‚ 1 7 -10 ˆ ‚ 4 ‚ 4 7 ‚ 11 -15 ˆ ‚ 7 7 ‚ ‚ -20 ˆ ‚ 7 7 ‚ 1 1 ‚ -25 ˆ ‚ Šˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒ -20 -15 -10 -5 0 5 10 15 20

PCO2

NOTE: 2 obs hidden.

18:24 Saturday, November 21, 2009 113

Page 59: R Code for Calculating Beale’s F-Type Statistic: c1

Cities in their Clusters

Obs city O3April O3May O3June O3July O3Aug O3Sep CLUSTER CLUSNAME

1 Lincoln 3.05017 3.8878 0.5766 1.2496 -3.6920 -2.7020 1 CL27 2 Oakland 9.22982 8.3519 0.9472 1.2300 -2.9679 0.5575 1 CL27 3 San Jose 8.75283 8.2189 -0.0051 1.6848 -3.9427 -1.0731 1 CL27 4 St. Petersburg 9.64822 6.5928 -5.1627 -2.3514 -2.4759 1.1570 1 CL27 5 Tacoma 7.19013 5.7665 -1.5010 -0.3845 -3.4556 -0.7950 1 CL27 6 Tampa 9.92602 7.3299 -4.6847 -3.0803 -2.3865 1.7117 1 CL27 7 Akron -2.59742 2.9776 9.3160 10.1753 -1.3167 -5.4473 2 CL13 8 Arlington -5.77401 3.3453 6.7535 13.4359 8.1736 -6.5235 2 CL13 9 Buffalo 2.51458 9.0380 13.3186 15.9207 1.0480 0.3954 2 CL13 10 Chicago 1.25153 6.0385 7.6226 7.0373 -0.5158 0.0429 2 CL13 11 Cincinnati -3.08945 3.1260 4.7007 5.7707 0.9676 -4.9646 2 CL13 12 Cleveland -4.30625 3.4514 9.1086 9.1632 0.2957 -4.3639 2 CL13 13 ColumbusOH -3.24023 5.2574 14.5176 7.3581 2.5967 -7.1603 2 CL13 14 Dayton -3.47475 2.9661 8.3600 8.3384 0.7234 -3.7851 2 CL13 15 Fort Wayne -4.89325 2.5078 6.7268 6.3050 -5.7237 -5.0256 2 CL13 16 Grand Rapids -3.30959 3.9831 8.5222 7.1289 -6.8933 -9.5720 2 CL13 17 Indianapolis -6.14490 2.6241 4.6211 4.1704 -3.3937 -2.3107 2 CL13 18 Johnstown 0.84099 7.3021 5.8602 10.3271 -1.5896 -6.2976 2 CL13 19 New York -0.85701 0.3905 7.4703 15.8371 6.1029 -3.1651 2 CL13 20 Pittsburgh -0.36179 4.9377 10.6607 14.6198 2.4950 -2.8201 2 CL13 21 Syracuse 1.04130 6.9690 12.5221 12.5066 -0.1769 1.0708 2 CL13 22 Toledo -5.91671 -1.5588 9.1269 8.0693 -0.3838 -3.3277 2 CL13 23 Denver 6.96790 12.1597 8.0521 11.4697 6.8247 -1.1549 3 CL17 24 El Paso 9.70463 9.3137 7.6609 5.2615 5.6874 0.4456 3 CL17 25 Kansas CityKS 4.28449 10.5564 7.0183 11.9288 8.9702 1.9942 3 CL17 26 Las Vegas 8.86449 15.7920 15.3006 5.3280 5.5927 -0.3099 3 CL17 27 Los Angeles 5.58612 10.9744 9.0467 5.5017 5.2416 2.4389 3 CL17 28 Modesto 7.20520 10.4089 8.5813 12.2299 4.5215 7.4796 3 CL17 29 Phoenix 7.66572 11.8096 8.4950 8.8198 9.5064 -0.6348 3 CL17 30 Riverside 5.01962 14.2865 15.4135 8.7508 8.3247 3.6302 3 CL17 31 Sacramento 6.71122 7.9368 5.9901 7.9478 4.2798 8.0364 3 CL17 32 San Bernardino 3.62120 12.9680 15.0344 8.3781 9.9923 1.1010 3 CL17 33 Santa Ana/Anaheim 9.37348 14.2964 10.1229 4.6612 6.4446 4.6599 3 CL17 34 Stockton 7.35334 8.1715 5.1208 7.3916 2.5567 5.3487 3 CL17 35 Atlanta -4.00079 2.8535 -1.9897 -0.0305 13.6344 2.2994 4 CL12 36 Charlotte 0.53066 2.7441 4.2031 3.6292 12.7265 -6.9343 4 CL12 37 ColumbusGA -2.64460 2.9716 -2.1978 -5.9310 7.2687 6.1511 4 CL12 38 Evansville -8.25527 1.0679 2.0634 2.7001 2.6426 -0.4325 4 CL12 39 Jackson 0.10213 3.5189 -2.0668 -5.8030 10.5212 1.5682 4 CL12 40 Kansas CityMO -1.13202 5.7234 0.9810 5.5242 3.4300 -3.1669 4 CL12 41 Knoxville 1.39910 5.3193 3.9502 -0.0561 7.6415 -0.0521 4 CL12 42 Lexington -6.40648 3.4592 3.4754 5.2706 7.5647 1.0119 4 CL12 43 Louisville -1.95398 3.5216 3.0344 3.9898 5.7273 -1.2057 4 CL12 44 Memphis -2.24268 3.4254 0.2333 -1.4341 11.6956 1.0011 4 CL12 45 St. Louis -0.48566 4.1664 1.4408 8.4464 5.2479 -1.9683 4 CL12 46 Bakersfield 2.01369 10.1284 14.0376 13.9645 9.5357 16.2752 5 CL55 47 Fresno 4.01151 12.9835 14.8018 16.4152 9.8696 13.5157 5 CL55 48 Dallas/Fort Worth 3.47606 5.2499 1.2840 0.5819 19.9481 9.1287 6 CL18 49 Huntsville 3.96797 9.1020 6.4593 3.3874 15.2416 10.0658 6 CL18 50 Little Rock 2.31853 8.3827 2.2919 0.9441 16.0051 5.4395 6 CL18

18:24 Saturday, November 21, 2009 114 Cities in their Clusters

Obs city O3April O3May O3June O3July O3Aug O3Sep CLUSTER CLUSNAME

51 Nashville 5.99371 8.8557 10.2495 5.6462 11.4303 5.2406 6 CL18 52 Oklahoma City 5.96884 11.1463 2.9474 6.2657 20.3420 5.5170 6 CL18 53 Shreveport 5.17327 6.0310 1.6275 -0.7434 13.2357 3.1967 6 CL18 54 Wichita 5.00061 10.3495 0.0144 9.1460 16.5816 3.6771 6 CL18 55 Austin 8.26811 2.1398 -5.5971 -11.3581 9.2746 11.6430 7 CL11 56 Baton Rouge 4.48913 13.4318 0.1609 -3.6472 8.2088 3.4473 7 CL11 57 Houston 6.53232 6.4918 -4.4637 -7.1414 7.2114 8.3122 7 CL11 58 Lafayette 6.51440 8.3299 -2.7520 -5.1370 5.5211 3.6854 7 CL11 59 Lake Charles 6.32986 3.9044 -6.4831 -12.5135 3.5228 6.4176 7 CL11

Page 60: R Code for Calculating Beale’s F-Type Statistic: c1

60 San Antonio 6.96342 5.3762 -1.3773 -8.6641 2.1612 9.4445 7 CL11 61 Boston 6.72094 2.6733 7.3469 7.7088 3.5155 -3.5027 8 CL28 62 Colorado Springs 8.53664 8.9151 5.4381 5.8312 2.1564 -2.5394 8 CL28 63 Kingston 8.25349 6.4617 7.5877 3.5178 -3.3418 -2.3785 8 CL28 64 Worcester 6.90519 2.5181 8.5516 7.6622 -1.8237 -7.1056 8 CL28 65 Jersey City 4.06688 5.1239 11.9726 21.1476 9.2866 -2.5867 9 CL25 66 Philadelphia 7.16699 10.1299 10.4305 18.1820 10.9228 -1.0916 9 CL25 67 Washington 2.21860 10.2754 12.0268 19.8456 16.1971 1.9847 9 CL25 68 Corpus Christi 5.98796 4.8851 -5.2161 -13.0445 -5.0587 7.7383 10 CL15 69 Miami 7.48433 7.7844 -8.5097 -12.2927 -8.1683 -2.3517 10 CL15 70 Omaha -0.40624 0.8112 -0.8071 4.5477 -1.0881 6.4413 11 Omaha

18:24 Saturday, November 21, 2009 115 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Eigenvalues of the Covariance Matrix

Eigenvalue Difference Proportion Cumulative

1 285.283713 203.395757 0.5998 0.5998 2 81.887956 39.494856 0.1722 0.7720 3 42.393101 13.859056 0.0891 0.8612 4 28.534044 14.839302 0.0600 0.9212 5 13.694742 4.186735 0.0288 0.9500 6 9.508008 2.984154 0.0200 0.9700 7 6.523854 2.367906 0.0137 0.9837 8 4.155948 2.266869 0.0087 0.9924 9 1.889079 1.064172 0.0040 0.9964 10 0.824907 0.355112 0.0017 0.9981 11 0.469796 0.042433 0.0010 0.9991 12 0.427363 0.0009 1.0000

Root-Mean-Square Total-Sample Standard Deviation = 6.295451 Root-Mean-Square Distance Between Observations = 30.84129

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

69 St. Petersburg Tampa 2 0.0000 1.00 . . 569 . 0.0422 68 Oakland San Jose 2 0.0001 1.00 . . 294 . 0.0723 67 Akron Cleveland 2 0.0002 1.00 . . 161 . 0.1118 66 Sacramento Stockton 2 0.0002 1.00 . . 131 . 0.1136 65 Buffalo Syracuse 2 0.0004 .999 . . 90.0 . 0.1656 64 Cincinnati Dayton 2 0.0004 .999 . . 75.0 . 0.1662 63 Los Angeles Santa Ana/Anaheim 2 0.0005 .998 . . 63.3 . 0.188 62 Bakersfield Fresno 2 0.0005 .998 . . 56.4 . 0.1934 61 Houston Lafayette 2 0.0006 .997 . . 51.7 . 0.1988 60 Louisville St. Louis 2 0.0006 .997 . . 48.5 . 0.2011

18:24 Saturday, November 21, 2009 116 Clustering based on Monthly Average Temperature and Ozone

Page 61: R Code for Calculating Beale’s F-Type Statistic: c1

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

59 Modesto CL66 3 0.0008 .996 . . 44.4 4.1 0.2083 58 Jackson Memphis 2 0.0006 .995 . . 42.9 . 0.2089 57 CL67 Toledo 3 0.0008 .994 . . 40.5 4.5 0.2123 56 Evansville Lexington 2 0.0007 .994 . . 39.2 . 0.2268 55 CL64 Indianapolis 3 0.0009 .993 . . 37.5 2.3 0.2332 54 Little Rock Shreveport 2 0.0008 .992 . . 36.6 . 0.2367 53 Jersey City Philadelphia 2 0.0008 .991 . . 36.0 . 0.2396 52 CL57 Fort Wayne 4 0.0011 .990 . . 34.5 2.3 0.2516 51 ColumbusGA CL58 3 0.0011 .989 . . 33.6 1.7 0.2562 50 CL61 San Antonio 3 0.0011 .988 . . 32.8 1.9 0.2584 49 Boston Worcester 2 0.0010 .987 . . 32.4 . 0.2685 48 Chicago Johnstown 2 0.0011 .986 . . 31.9 . 0.2798 47 CL65 Pittsburgh 3 0.0014 .984 . . 30.9 3.6 0.2855 46 CL50 Lake Charles 4 0.0014 .983 . . 30.3 1.6 0.2873 45 CL68 Tacoma 3 0.0016 .981 . . 29.5 20.9 0.2882 44 Huntsville Nashville 2 0.0012 .980 . . 29.5 . 0.2901 43 Colorado Springs Denver 2 0.0013 .979 . . 29.5 . 0.2961 42 CL52 CL55 7 0.0031 .976 . . 27.3 4.5 0.3088 41 Knoxville CL60 3 0.0017 .974 . . 27.0 3.0 0.3172 40 CL53 Washington 3 0.0019 .972 . . 26.6 2.3 0.3364 39 Oklahoma City Wichita 2 0.0017 .970 . . 26.6 . 0.338

18:24 Saturday, November 21, 2009 117 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

38 Atlanta CL51 4 0.0021 .968 . . 26.3 2.5 0.3391 37 CL56 Kansas CityMO 3 0.0020 .966 . . 26.2 2.7 0.3408

Page 62: R Code for Calculating Beale’s F-Type Statistic: c1

36 Austin CL46 5 0.0021 .964 . . 26.0 2.1 0.3447 35 CL49 CL48 4 0.0024 .962 . . 25.8 2.2 0.3467 34 Arlington New York 2 0.0018 .960 . . 26.1 . 0.3519 33 CL37 CL41 6 0.0030 .957 . . 25.6 2.4 0.3564 32 Las Vegas Riverside 2 0.0019 .955 . . 26.0 . 0.3576 31 Lincoln Omaha 2 0.0019 .953 . . 26.4 . 0.3638 30 Dallas/Fort Worth CL54 3 0.0023 .951 . . 26.6 2.9 0.3665 29 CL42 Grand Rapids 8 0.0030 .948 . . 26.6 2.7 0.3866 28 CL40 Kansas CityKS 4 0.0027 .945 . . 26.8 1.9 0.3924 27 CL35 CL47 7 0.0049 .940 . . 26.0 3.9 0.4003 26 Corpus Christi Miami 2 0.0023 .938 . . 26.5 . 0.4022 25 CL63 CL59 5 0.0051 .933 . . 26.0 10.4 0.4092 24 CL29 ColumbusOH 9 0.0035 .929 . . 26.2 2.6 0.4225 23 CL26 CL69 4 0.0041 .925 . . 26.4 3.5 0.429 22 Charlotte CL33 7 0.0035 .921 . . 26.8 2.2 0.4335 21 CL36 Baton Rouge 6 0.0042 .917 . . 27.2 3.2 0.4557 20 CL25 San Bernardino 6 0.0040 .913 . . 27.7 2.4 0.4602 19 CL38 CL30 7 0.0073 .906 . . 27.3 5.3 0.4632 18 CL44 CL39 4 0.0048 .901 . . 27.9 3.3 0.4635

18:24 Saturday, November 21, 2009 118 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

17 CL24 CL27 16 0.0135 .888 . . 26.2 7.7 0.4734 16 Kingston CL31 3 0.0038 .884 . . 27.4 2.0 0.4795 15 El Paso CL32 3 0.0041 .880 . . 28.8 2.2 0.4926 14 CL34 CL22 9 0.0076 .872 .840 3.33 29.4 4.0 0.5064 13 CL21 CL23 10 0.0126 .860 .829 2.88 29.1 6.4 0.5399 12 CL17 CL16 19 0.0120 .848 .818 2.64 29.3 4.7 0.5581 11 CL19 CL18 11 0.0191 .829 .806 1.87 28.5 7.9 0.6282 10 CL15 Phoenix 4 0.0072 .821 .793 2.32 30.7 2.4 0.6337 9 CL28 CL20 10 0.0207 .801 .777 1.76 30.6 10.3 0.6362

Page 63: R Code for Calculating Beale’s F-Type Statistic: c1

8 CL12 CL14 28 0.0420 .759 .760 -.09 27.8 14.3 0.6471 7 CL62 CL9 12 0.0153 .743 .740 0.25 30.4 4.1 0.6729 6 CL43 CL45 5 0.0165 .727 .715 0.66 34.1 16.9 0.7181 5 CL8 CL7 40 0.0708 .656 .684 -1.4 31.0 15.7 0.7668 4 CL11 CL10 15 0.0377 .618 .642 -1.1 35.6 9.1 0.828 3 CL4 CL13 25 0.0808 .538 .579 -1.5 38.9 15.4 0.8797 2 CL5 CL6 45 0.0824 .455 .460 -.13 56.8 13.6 0.9913 1 CL2 CL3 70 0.4551 .000 .000 0.00 . 56.8 1.2321

18:24 Saturday, November 21, 2009 119 Clustering based on Monthly Average Temperature and Ozone

Plot of _CCC_*_NCL_. Symbol is value of _NCL_.

‚ 4 ˆ ‚ ‚ ‚ ‚ ‚ 1 ‚ 3 ˆ C ‚ 1 u ‚ b ‚ 1 i ‚ c ‚ 1 ‚ C 2 ˆ l ‚ 1 u ‚ 9 s ‚ t ‚ e ‚ r ‚ i 1 ˆ n ‚ g ‚ 6 ‚ C ‚ r ‚ 7 i ‚ t 0 ˆ 1 e ‚ 2 8 r ‚ i ‚ o ‚ n ‚ ‚ -1 ˆ ‚ 4 ‚ 5 ‚ ‚ 3 ‚ ‚ -2 ˆ Šƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒ 0 10 20 30 40 50 60 70

Page 64: R Code for Calculating Beale’s F-Type Statistic: c1

Number of Clusters

NOTE: 125 obs had missing values.

18:24 Saturday, November 21, 2009 120 Clustering based on Monthly Average Temperature and Ozone 4 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=4 Maxiter=1

Initial Seeds

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 48.76666667 52.09677419 58.33333333 62.67741935 65.03225806 61.03333333 2 53.16666667 63.00000000 71.10000000 78.67741935 75.67741935 67.33333333 3 66.13333333 80.03225806 89.13333333 91.45161290 93.22580645 87.63333333 4 78.00000000 78.83870968 81.06666667 84.16129032 83.80645161 82.10000000

Initial Seeds

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 7.19013409 5.76648873 -1.50100552 -0.38450774 -3.45561888 -0.79503158 2 2.21860178 10.27544411 12.02678501 19.84557496 16.19708024 1.98466104 3 7.66572201 11.80961340 8.49498390 8.81982164 9.50636708 -0.63483665 4 7.48432721 7.78439194 -8.50971825 -12.29273944 -8.16825369 -2.35173186

Criterion Based on Final Seeds = 3.9178

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 11 4.2099 18.4836 2 18.0678 2 35 4.0895 21.8517 1 18.0678 3 12 4.0930 19.2151 4 20.2164 4 12 3.1739 16.4983 3 20.2164

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ TempApril 8.63420 3.58228 0.835348 5.073400 TempMay 6.63611 2.80236 0.829425 4.862521 TempJune 6.05594 3.18264 0.735816 2.785238 TempJuly 5.36010 3.76332 0.528490 1.120844 TempAug 6.95429 3.31603 0.782517 3.598058 TempSep 6.41754 3.42381 0.727745 2.673026 O3April 4.87097 4.59173 0.150002 0.176474 O3May 3.80274 3.74238 0.073604 0.079452 O3June 5.97917 4.33973 0.496106 0.984544 O3July 7.59798 4.63757 0.643649 1.806219

18:24 Saturday, November 21, 2009 121 Clustering based on Monthly Average Temperature and Ozone 4 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=4 Maxiter=1

Statistics for Variables

Page 65: R Code for Calculating Beale’s F-Type Statistic: c1

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ O3Aug 6.53520 5.02865 0.433657 0.765715 O3Sep 5.26091 4.56564 0.279596 0.388110 OVER-ALL 6.29545 3.97134 0.619360 1.627153

Pseudo F Statistic = 35.80

Approximate Expected Over-All R-Squared = 0.29082

Cubic Clustering Criterion = 27.953

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 49.24671717 57.96456500 65.89040404 71.94623656 68.33919843 62.85151515 2 55.15488889 64.08878648 72.29146032 78.61342550 74.54233487 68.80215873 3 65.00873016 72.24654378 79.93670635 84.07949309 84.88056836 76.84484127 4 72.84444444 76.15994624 81.15555556 82.97849462 85.32661290 78.95138889

Cluster Means

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 3.69758351 6.05352022 4.77133841 5.69810499 -2.03855381 -3.74136546 2 1.10057721 6.19532135 7.60732865 9.26417159 5.03996545 0.39237546 3 4.32578140 8.85402774 5.83110597 3.56477483 12.55367256 3.75165367 4 5.80010879 6.06306603 -4.02917863 -7.58035535 2.96670468 4.91036609

Cluster Standard Deviations

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.121536484 3.805748527 5.031814888 6.678800959 3.011353105 2.467708853 2 3.934195829 2.271364692 2.520751302 3.232875244 3.567428831 3.434815562 3 2.655702245 3.498801109 4.075126855 3.398531735 4.024752704 4.723897873 4 2.580671486 2.400911700 1.229217813 0.754682457 1.482278327 2.452966235

18:24 Saturday, November 21, 2009 122 Clustering based on Monthly Average Temperature and Ozone 4 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=4 Maxiter=1

Cluster Standard Deviations

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 5.327931072 3.171683126 3.995092087 4.170524160 3.785561664 3.160767453 2 4.771176291 3.995518374 4.387663429 5.241756013 4.999302363 5.316745190 3 4.097936885 4.029076812 5.748855442 3.623129765 4.869887843 3.485385040 4 3.680081275 3.051228802 2.436336539 3.895790304 6.142412947 4.057940470

18:24 Saturday, November 21, 2009 123 Clustering based on Monthly Average Temperature and Ozone 4 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Page 66: R Code for Calculating Beale’s F-Type Statistic: c1

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 12893.41 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 124 Clustering based on Monthly Average Temperature and Ozone 10 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=10 Maxiter=1

Initial Seeds

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 48.76666667 52.09677419 58.33333333 62.67741935 65.03225806 61.03333333 2 78.00000000 78.83870968 81.06666667 84.16129032 83.80645161 82.10000000 3 68.28333333 73.88709677 82.11666667 86.04838710 90.20967742 79.26666667 4 49.06666667 61.22580645 69.56666667 74.90322581 68.00000000 62.96666667 5 58.06666667 66.64516129 73.90000000 80.22580645 77.87096774 77.23333333 6 53.56666667 63.54838710 74.36666667 81.09677419 76.54838710 69.53333333 7 61.20000000 75.58064516 85.46666667 88.41935484 88.19354839 81.93333333 8 58.81666667 63.38709677 65.66666667 71.51612903 70.09677419 68.60000000 9 62.23333333 65.96774194 73.63333333 79.06451613 79.67741935 69.36666667 10 51.55555556 62.25806452 70.82222222 80.68817204 73.35483871 64.08888889

Initial Seeds

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 7.19013409 5.76648873 -1.50100552 -0.38450774 -3.45561888 -0.79503158 2 7.48432721 7.78439194 -8.50971825 -12.29273944 -8.16825369 -2.35173186 3 3.47606096 5.24987066 1.28404527 0.58188360 19.94808850 9.12871030 4 -3.30958634 3.98311820 8.52224439 7.12891093 -6.89333214 -9.57197828 5 2.01369361 10.12843346 14.03764848 13.96454628 9.53565765 16.27516873 6 4.06688135 5.12388166 11.97256249 21.14757640 9.28659646 -2.58668876 7 8.86449487 15.79199284 15.30057713 5.32796804 5.59274612 -0.30986960 8 9.37348405 14.29642133 10.12286454 4.66115447 6.44455839 4.65990880 9 0.53066296 2.74408439 4.20306990 3.62915275 12.72652324 -6.93428130 10 -0.40624116 0.81119803 -0.80711924 4.54770896 -1.08807176 6.44134763

Criterion Based on Final Seeds = 2.7042

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4 2.9366 13.8596 4 22.9418 2 9 2.8101 14.6155 3 18.2404 3 8 2.7773 12.6844 9 16.0047 4 15 2.8638 20.1393 10 12.4500 5 2 1.2173 2.9818 8 19.0119 6 5 2.5129 10.0314 9 16.4453 7 4 3.4654 13.3569 3 20.4409 8 6 2.4102 11.5659 6 16.8092

18:24 Saturday, November 21, 2009 125 Clustering based on Monthly Average Temperature and Ozone 10 Clusters, NH method

The FASTCLUS Procedure

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Replace=FULL Radius=0 Maxclusters=10 Maxiter=1

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 9 10 3.2979 16.4383 10 15.6403 10 7 2.6906 11.5433 4 12.4500

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ TempApril 8.63420 2.71109 0.914267 10.664167 TempMay 6.63611 1.78292 0.937232 14.931587 TempJune 6.05594 2.09750 0.895686 8.586458 TempJuly 5.36010 2.08021 0.869030 6.635326 TempAug 6.95429 2.26374 0.907859 9.852982 TempSep 6.41754 2.20784 0.897080 8.716245 O3April 4.87097 3.65227 0.511125 1.045512 O3May 3.80274 3.00564 0.456770 0.840840 O3June 5.97917 2.86279 0.800658 4.016514 O3July 7.59798 3.23390 0.842472 5.348062 O3Aug 6.53520 4.01055 0.672515 2.053573 O3Sep 5.26091 3.43973 0.628268 1.690109 OVER-ALL 6.29545 2.86062 0.820457 4.569700

Pseudo F Statistic = 30.46

Approximate Expected Over-All R-Squared = 0.51400

Cubic Clustering Criterion = 39.188

WARNING: The two values above are invalid for correlated variables.

18:24 Saturday, November 21, 2009 126 Clustering based on Monthly Average Temperature and Ozone 10 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=10 Maxiter=1

Cluster Means

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 50.22500000 54.23387097 60.25833333 64.59677420 65.56451613 61.66666667 2 73.81481481 77.28315412 81.70000000 83.29390681 85.56272401 80.07407407 3 68.30416667 72.05040323 79.49791667 83.05241936 84.76814516 75.76875000 4 49.63203704 60.93530466 70.14407407 76.37777778 69.87025090 64.74444445 5 58.40000000 67.43548387 75.05000000 80.46774194 78.25806452 77.33333333 6 53.45777778 63.53440860 72.85222222 80.80645161 76.73440860 68.48333333 7 63.43452381 75.89285714 83.48928571 86.65783410 86.89170507 81.50952381 8 58.66462963 64.53315412 69.51777778 73.64103943 73.25949821 71.63388889 9 60.13333333 67.10000000 75.01000000 81.40967742 79.72258065 70.48333333 10 54.15396826 63.48079877 72.58571429 80.27342550 74.30568357 66.65555556

Cluster Means

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 8.42735652 7.81310810 1.21979265 2.09034770 -2.05246827 -0.96249425 2 7.51718232 5.87049292 -4.91627841 -8.39811544 1.06685456 5.30643024

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3 1.82997686 6.51416098 0.97405435 -1.58067614 12.76561087 4.99978721 4 -0.12383629 4.74806912 9.30752800 9.58602505 -0.06163228 -3.87025491 5 3.01260156 11.55598615 14.41971862 15.18985576 9.70263494 14.89545859 6 3.37599070 7.29521793 9.78368250 17.38821006 10.29590287 -0.57291501 7 7.81361623 12.80045074 11.71749727 7.04002120 7.27781689 0.78278207 8 6.64176001 10.79268081 8.98267494 7.68504968 5.50608850 4.84406018 9 0.02720004 5.57609041 3.40790411 5.57430505 10.90698730 0.10620526 10 -1.10345949 3.38600682 2.81762913 3.92581152 -0.63935013 -1.35912789

Cluster Standard Deviations

Cluster TempApril TempMay TempJune TempJuly TempAug TempSep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 5.863722432 1.760430487 1.980530232 4.489669031 2.353512662 2.844227424 2 1.999521548 1.238661140 0.673300330 0.573532702 1.638515285 1.581207149 3 2.120960211 1.645442223 1.655161179 1.701981420 2.710924355 1.544946641 4 3.183667616 2.526638315 2.423236340 2.041659618 1.465037018 2.121486617 5 0.471404516 1.117684911 1.626345597 0.342148444 0.547437509 0.141421356 6 0.313620829 0.734019641 1.175965588 1.263223501 1.026498830 1.840063405 7 2.040516936 2.877378353 4.669900686 4.321909775 5.034043531 4.909729336 8 0.391858766 1.257432139 2.989304390 1.964393465 2.478754371 2.357696486 9 3.044566096 1.243826240 1.196708449 1.894369163 2.657163088 1.794109017 10 2.421376240 1.339068978 1.634047644 0.792808299 1.476461387 2.075369967

18:24 Saturday, November 21, 2009 127 Clustering based on Monthly Average Temperature and Ozone 10 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=10 Maxiter=1

Cluster Standard Deviations

Cluster O3April O3May O3June O3July O3Aug O3Sep ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 0.874175643 1.397390871 2.987298702 2.647224803 2.833962451 1.269819397 2 1.455130452 1.992115061 2.044770243 4.177042595 5.910572564 4.539734083 3 3.055716615 3.604273431 2.748118412 3.326926442 4.235830128 3.330760554 4 4.381407402 3.266728038 2.454737455 2.902769426 3.400267179 3.054225587 5 1.412669166 2.018864375 0.540328774 1.732849278 0.236141549 1.951204792 6 2.955176005 4.470528901 2.410417628 3.640483355 3.727408867 2.458412706 7 2.041939453 2.845878277 4.216627152 2.015643637 1.952036170 1.951496565 8 1.925052872 2.538308612 3.520163215 2.653394805 2.539635250 2.728416378 9 4.633593049 3.261455863 3.396100492 4.120355220 4.948672508 4.391789114 10 5.564782327 2.153533841 2.934143540 1.593519207 3.008924889 3.690570351

18:24 Saturday, November 21, 2009 128 Clustering based on Monthly Average Temperature and Ozone 10 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 6142.87 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 129 Cities in their Clusters

Temp Temp Temp Obs city April TempMay June July TempAug TempSep O3April

1 St. Petersburg 74.6000 78.0323 81.4000 83.8065 84.0000 81.0333 9.64822

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2 Tampa 74.6000 78.0323 81.4000 83.8065 84.0000 81.0333 9.92602 3 Houston 73.1667 76.7742 82.1667 83.3226 87.0968 78.1667 6.53232 4 Lafayette 73.4000 76.9032 81.5667 82.5161 85.7419 78.4333 6.51440 5 San Antonio 71.4333 76.3548 82.0667 83.0968 86.4194 80.5667 6.96342 6 Lake Charles 72.2333 75.1290 80.7000 82.5484 86.0968 77.8667 6.32986 7 Austin 72.0000 76.6452 81.9667 83.4516 88.5161 81.6667 8.26811 8 Corpus Christi 74.9000 78.8387 82.9667 82.9355 84.3871 79.8000 5.98796 9 Miami 78.0000 78.8387 81.0667 84.1613 83.8065 82.1000 7.48433 10 Baton Rouge 72.0333 74.7419 80.5000 81.8710 85.2903 76.3000 4.48913 11 Oakland 54.8000 55.6774 59.8333 62.1935 64.0968 63.8667 9.22982 12 San Jose 54.8000 55.6774 59.8333 62.1935 64.0968 63.8667 8.75283 13 Tacoma 48.7667 52.0968 58.3333 62.6774 65.0323 61.0333 7.19013 14 Akron 51.4000 61.6129 70.0667 76.0968 68.4516 63.7333 -2.59742 15 Cleveland 50.5667 61.2581 70.4000 76.4194 69.3548 65.1667 -4.30625 16 Buffalo 46.1333 59.8387 68.5667 74.5806 68.0645 64.4667 2.51458 17 Syracuse 46.8333 60.9032 69.9667 75.1613 69.0968 65.1000 1.04130 18 Cincinnati 55.3000 63.7742 73.2667 79.1935 72.9677 67.0667 -3.08945 19 Dayton 53.8333 63.8065 72.7333 78.6452 71.5806 67.0000 -3.47475 20 Toledo 50.9000 62.8387 71.0333 77.4516 69.9677 65.3333 -5.91671 21 Indianapolis 55.2667 64.5484 74.0000 79.5161 72.6129 67.2667 -6.14490 22 Fort Wayne 51.5000 62.5806 71.6333 78.6129 69.7419 64.5667 -4.89325

Obs O3May O3June O3July O3Aug O3Sep CLUSTER CLUSNAME

1 6.5928 -5.1627 -2.3514 -2.4759 1.1570 1 CL13 2 7.3299 -4.6847 -3.0803 -2.3865 1.7117 1 CL13 3 6.4918 -4.4637 -7.1414 7.2114 8.3122 1 CL13 4 8.3299 -2.7520 -5.1370 5.5211 3.6854 1 CL13 5 5.3762 -1.3773 -8.6641 2.1612 9.4445 1 CL13 6 3.9044 -6.4831 -12.5135 3.5228 6.4176 1 CL13 7 2.1398 -5.5971 -11.3581 9.2746 11.6430 1 CL13 8 4.8851 -5.2161 -13.0445 -5.0587 7.7383 1 CL13 9 7.7844 -8.5097 -12.2927 -8.1683 -2.3517 1 CL13 10 13.4318 0.1609 -3.6472 8.2088 3.4473 1 CL13 11 8.3519 0.9472 1.2300 -2.9679 0.5575 2 CL45 12 8.2189 -0.0051 1.6848 -3.9427 -1.0731 2 CL45 13 5.7665 -1.5010 -0.3845 -3.4556 -0.7950 2 CL45 14 2.9776 9.3160 10.1753 -1.3167 -5.4473 3 CL12 15 3.4514 9.1086 9.1632 0.2957 -4.3639 3 CL12 16 9.0380 13.3186 15.9207 1.0480 0.3954 3 CL12 17 6.9690 12.5221 12.5066 -0.1769 1.0708 3 CL12 18 3.1260 4.7007 5.7707 0.9676 -4.9646 3 CL12 19 2.9661 8.3600 8.3384 0.7234 -3.7851 3 CL12 20 -1.5588 9.1269 8.0693 -0.3838 -3.3277 3 CL12 21 2.6241 4.6211 4.1704 -3.3937 -2.3107 3 CL12 22 2.5078 6.7268 6.3050 -5.7237 -5.0256 3 CL12

18:24 Saturday, November 21, 2009 130 Cities in their Clusters

Temp Temp Temp Obs city April TempMay June July TempAug TempSep O3April

23 Boston 49.4000 58.4194 71.2000 76.0323 71.6452 67.3667 6.72094 24 Worcester 47.3889 58.7312 68.9111 73.3978 69.3441 65.3778 6.90519 25 Chicago 49.8000 61.8710 70.5667 78.5806 70.5484 63.6667 1.25153 26 Johnstown 47.8000 60.3226 69.7667 76.0000 69.0968 64.9333 0.84099 27 Pittsburgh 52.1000 61.2581 69.6000 76.2581 69.1935 64.4000 -0.36179 28 Lincoln 51.0667 61.8710 70.4000 80.8387 74.1935 64.1333 3.05017 29 Omaha 51.5556 62.2581 70.8222 80.6882 73.3548 64.0889 -0.40624 30 Grand Rapids 49.0667 61.2258 69.5667 74.9032 68.0000 62.9667 -3.30959 31 ColumbusOH 55.1667 65.0323 74.7333 80.3548 73.3226 68.1000 -3.24023 32 Kingston 53.0889 62.6237 73.0778 80.8710 75.8495 69.5667 8.25349 33 Sacramento 58.3267 64.2581 71.2067 73.6258 74.4387 73.2867 6.71122 34 Stockton 58.2222 64.5484 71.5667 74.1183 74.5161 73.0222 7.35334 35 Los Angeles 58.8167 63.3871 65.6667 71.5161 70.0968 68.6000 5.58612 36 Santa Ana/Anaheim 58.8167 63.3871 65.6667 71.5161 70.0968 68.6000 9.37348 37 Modesto 58.5167 64.8226 71.7333 74.3387 74.9032 73.4167 7.20520

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38 San Bernardino 59.2889 66.7957 71.2667 76.7312 75.5054 72.8778 3.62120 39 Bakersfield 58.0667 66.6452 73.9000 80.2258 77.8710 77.2333 2.01369 40 Fresno 58.7333 68.2258 76.2000 80.7097 78.6452 77.4333 4.01151 41 Louisville 59.5000 67.8065 76.5000 83.4839 78.7742 72.2667 -1.95398 42 St. Louis 58.8000 67.0323 75.0667 83.1613 76.7419 69.9667 -0.48566 43 Evansville 58.0000 65.6452 74.7667 79.6452 74.6129 68.5000 -8.25527 44 Lexington 56.7000 65.5161 73.6667 79.8065 75.9355 68.9333 -6.40648

Obs O3May O3June O3July O3Aug O3Sep CLUSTER CLUSNAME

23 2.6733 7.3469 7.7088 3.5155 -3.5027 3 CL12 24 2.5181 8.5516 7.6622 -1.8237 -7.1056 3 CL12 25 6.0385 7.6226 7.0373 -0.5158 0.0429 3 CL12 26 7.3021 5.8602 10.3271 -1.5896 -6.2976 3 CL12 27 4.9377 10.6607 14.6198 2.4950 -2.8201 3 CL12 28 3.8878 0.5766 1.2496 -3.6920 -2.7020 3 CL12 29 0.8112 -0.8071 4.5477 -1.0881 6.4413 3 CL12 30 3.9831 8.5222 7.1289 -6.8933 -9.5720 3 CL12 31 5.2574 14.5176 7.3581 2.5967 -7.1603 3 CL12 32 6.4617 7.5877 3.5178 -3.3418 -2.3785 3 CL12 33 7.9368 5.9901 7.9478 4.2798 8.0364 4 CL20 34 8.1715 5.1208 7.3916 2.5567 5.3487 4 CL20 35 10.9744 9.0467 5.5017 5.2416 2.4389 4 CL20 36 14.2964 10.1229 4.6612 6.4446 4.6599 4 CL20 37 10.4089 8.5813 12.2299 4.5215 7.4796 4 CL20 38 12.9680 15.0344 8.3781 9.9923 1.1010 4 CL20 39 10.1284 14.0376 13.9645 9.5357 16.2752 5 CL62 40 12.9835 14.8018 16.4152 9.8696 13.5157 5 CL62 41 3.5216 3.0344 3.9898 5.7273 -1.2057 6 CL14 42 4.1664 1.4408 8.4464 5.2479 -1.9683 6 CL14 43 1.0679 2.0634 2.7001 2.6426 -0.4325 6 CL14 44 3.4592 3.4754 5.2706 7.5647 1.0119 6 CL14

18:24 Saturday, November 21, 2009 131 Cities in their Clusters

Temp Temp Temp Obs city April TempMay June July TempAug TempSep O3April

45 Knoxville 61.4000 66.3871 75.1333 78.8387 78.0000 70.1000 1.39910 46 Kansas CityMO 54.8000 63.6452 71.7667 81.1613 76.5484 65.9667 -1.13202 47 Arlington 56.7667 67.4839 74.9333 83.2258 79.9032 70.2667 -5.77401 48 New York 53.0889 62.6237 73.0778 80.8710 75.8495 69.5667 -0.85701 49 Charlotte 62.2333 65.9677 73.6333 79.0645 79.6774 69.3667 0.53066 50 Jackson 69.5000 71.7742 79.7000 82.1935 84.2258 75.3667 0.10213 51 Memphis 67.2667 71.4194 79.9000 83.9355 82.9032 75.4333 -2.24268 52 Little Rock 65.6833 71.1129 78.9000 84.4677 84.2097 75.1667 2.31853 53 Shreveport 69.6333 72.1935 80.0333 83.1290 86.1290 75.5000 5.17327 54 ColumbusGA 68.2667 71.8548 78.3667 82.0323 84.3387 75.0833 -2.64460 55 Huntsville 65.7667 69.4194 76.4667 80.7419 80.8387 74.0333 3.96797 56 Nashville 62.8333 67.9032 76.8000 82.1935 79.6129 72.0333 5.99371 57 Oklahoma City 61.5333 68.3226 75.9000 82.4194 84.9677 71.3667 5.96884 58 Wichita 56.2000 65.4516 73.3000 82.5161 81.4839 67.2333 5.00061 59 Atlanta 65.3667 69.1290 75.1667 79.3871 82.1290 73.3000 -4.00079 60 Dallas/Fort Worth 68.2833 73.8871 82.1167 86.0484 90.2097 79.2667 3.47606 61 Jersey City 53.5667 63.5484 74.3667 81.0968 76.5484 69.5333 4.06688 62 Philadelphia 53.8000 64.1613 73.1000 81.3871 77.7097 70.1667 7.16699 63 Washington 53.1667 63.0000 71.1000 78.6774 75.6774 67.3333 2.21860 64 Kansas CityKS 53.6667 64.3387 72.6167 82.0000 77.8871 65.8167 4.28449 65 Colorado Springs 42.5333 53.4839 63.0333 71.3226 69.0323 57.9000 8.53664 66 Denver 42.5917 54.3306 63.4167 73.1720 70.6452 58.9889 6.96790

Obs O3May O3June O3July O3Aug O3Sep CLUSTER CLUSNAME

45 5.3193 3.9502 -0.0561 7.6415 -0.0521 6 CL14 46 5.7234 0.9810 5.5242 3.4300 -3.1669 6 CL14 47 3.3453 6.7535 13.4359 8.1736 -6.5235 6 CL14

Page 71: R Code for Calculating Beale’s F-Type Statistic: c1

48 0.3905 7.4703 15.8371 6.1029 -3.1651 6 CL14 49 2.7441 4.2031 3.6292 12.7265 -6.9343 6 CL14 50 3.5189 -2.0668 -5.8030 10.5212 1.5682 7 CL11 51 3.4254 0.2333 -1.4341 11.6956 1.0011 7 CL11 52 8.3827 2.2919 0.9441 16.0051 5.4395 7 CL11 53 6.0310 1.6275 -0.7434 13.2357 3.1967 7 CL11 54 2.9716 -2.1978 -5.9310 7.2687 6.1511 7 CL11 55 9.1020 6.4593 3.3874 15.2416 10.0658 7 CL11 56 8.8557 10.2495 5.6462 11.4303 5.2406 7 CL11 57 11.1463 2.9474 6.2657 20.3420 5.5170 7 CL11 58 10.3495 0.0144 9.1460 16.5816 3.6771 7 CL11 59 2.8535 -1.9897 -0.0305 13.6344 2.2994 7 CL11 60 5.2499 1.2840 0.5819 19.9481 9.1287 7 CL11 61 5.1239 11.9726 21.1476 9.2866 -2.5867 8 CL28 62 10.1299 10.4305 18.1820 10.9228 -1.0916 8 CL28 63 10.2754 12.0268 19.8456 16.1971 1.9847 8 CL28 64 10.5564 7.0183 11.9288 8.9702 1.9942 8 CL28 65 8.9151 5.4381 5.8312 2.1564 -2.5394 9 CL43 66 12.1597 8.0521 11.4697 6.8247 -1.1549 9 CL43

18:24 Saturday, November 21, 2009 132 Cities in their Clusters

Temp Temp Temp Obs city April TempMay June July TempAug TempSep O3April

67 Las Vegas 61.2000 75.5806 85.4667 88.4194 88.1935 81.9333 8.86449 68 Riverside 62.9714 73.6037 79.1238 85.4378 84.6636 80.8048 5.01962 69 El Paso 63.4333 74.3548 80.2333 81.3226 81.4839 75.6667 9.70463 70 Phoenix 66.1333 80.0323 89.1333 91.4516 93.2258 87.6333 7.66572

Obs O3May O3June O3July O3Aug O3Sep CLUSTER CLUSNAME

67 15.7920 15.3006 5.3280 5.5927 -0.3099 10 CL10 68 14.2865 15.4135 8.7508 8.3247 3.6302 10 CL10 69 9.3137 7.6609 5.2615 5.6874 0.4456 10 CL10 70 11.8096 8.4950 8.8198 9.5064 -0.6348 10 CL10

18:24 Saturday, November 21, 2009 133 Clustering based on First two Temperature PCs

The CLUSTER Procedure Average Linkage Cluster Analysis

Eigenvalues of the Covariance Matrix

Eigenvalue Difference Proportion Cumulative

1 240.547597 218.394415 0.9157 0.9157 2 22.153182 0.0843 1.0000

Root-Mean-Square Total-Sample Standard Deviation = 11.46082 Root-Mean-Square Distance Between Observations = 22.92164

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

69 Kingston New York 2 0.0000 1.00 . . . . 0 T 68 Oakland San Jose 2 0.0000 1.00 . . . . 0 T 67 Los Angeles Santa Ana/Anaheim 2 0.0000 1.00 . . . . 0 T

Page 72: R Code for Calculating Beale’s F-Type Statistic: c1

66 St. Petersburg Tampa 2 0.0000 1.00 . . . . 0 65 Johnstown Syracuse 2 0.0000 1.00 . . 21E3 . 0.0161 64 Charlotte Knoxville 2 0.0000 1.00 . . 9903 . 0.0201 63 Lincoln Omaha 2 0.0000 1.00 . . 6999 . 0.0212 62 Corpus Christi CL66 3 0.0000 1.00 . . 5052 . 0.0225 61 Sacramento Stockton 2 0.0000 1.00 . . 4154 . 0.0265 60 Cincinnati Indianapolis 2 0.0000 1.00 . . 3436 . 0.0302 59 Fort Wayne Toledo 2 0.0000 1.00 . . 3019 . 0.0305 58 Houston San Antonio 2 0.0000 1.00 . . 2720 . 0.0317 57 Jersey City Philadelphia 2 0.0000 1.00 . . 2476 . 0.0336 56 Akron Pittsburgh 2 0.0000 1.00 . . 2300 . 0.0342 55 Kansas CityMO CL69 3 0.0000 1.00 . . 2067 . 0.035

18:24 Saturday, November 21, 2009 134 Clustering based on First two Temperature PCs

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

54 Evansville Lexington 2 0.0000 1.00 . . 1931 . 0.0389 53 Modesto CL61 3 0.0000 1.00 . . 1756 2.9 0.0415 52 Dayton Washington 2 0.0000 1.00 . . 1654 . 0.0433 51 Grand Rapids Worcester 2 0.0000 1.00 . . 1554 . 0.0464 50 Boston Cleveland 2 0.0000 1.00 . . 1471 . 0.0476 49 Fresno Nashville 2 0.0000 1.00 . . 1407 . 0.048 48 Atlanta Huntsville 2 0.0000 1.00 . . 1352 . 0.0495 47 ColumbusGA Jackson 2 0.0000 1.00 . . 1284 . 0.0544 46 El Paso Little Rock 2 0.0001 1.00 . . 1196 . 0.0625 45 Kansas CityKS CL55 4 0.0001 .999 . . 1061 7.6 0.0662 44 Baton Rouge Lake Charles 2 0.0001 .999 . . 1008 . 0.0667 43 CL58 Lafayette 3 0.0001 .999 . . 937 5.9 0.0686 42 CL46 Memphis 3 0.0001 .999 . . 876 1.6 0.0762 41 CL56 CL50 4 0.0002 .999 . . 777 6.1 0.0783 40 CL60 CL52 4 0.0002 .999 . . 698 8.4 0.0807 39 CL57 CL45 6 0.0002 .999 . . 614 7.0 0.0844

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38 Buffalo CL51 3 0.0001 .999 . . 592 4.2 0.0854 37 Chicago CL59 3 0.0001 .998 . . 573 10.3 0.0864 36 ColumbusOH CL39 7 0.0001 .998 . . 558 2.0 0.0875 35 Arlington St. Louis 2 0.0001 .998 . . 555 . 0.0889 34 Austin CL43 4 0.0002 .998 . . 543 3.0 0.0905

18:24 Saturday, November 21, 2009 135 Clustering based on First two Temperature PCs

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

33 CL38 CL65 5 0.0002 .998 . . 514 4.3 0.0938 32 Bakersfield CL64 3 0.0002 .998 . . 507 29.0 0.0943 31 CL47 Shreveport 3 0.0002 .997 . . 498 4.4 0.1027 30 CL49 Oklahoma City 3 0.0002 .997 . . 490 6.2 0.1061 29 CL34 CL62 7 0.0005 .997 . . 446 8.8 0.108 28 Colorado Springs Denver 2 0.0002 .997 . . 448 . 0.1141 27 CL41 CL37 7 0.0005 .996 . . 416 6.9 0.1159 26 CL35 Wichita 3 0.0002 .996 . . 420 1.9 0.1159 25 CL53 San Bernardino 4 0.0003 .996 . . 418 14.5 0.1172 24 CL30 Louisville 4 0.0003 .995 . . 419 2.4 0.1265 23 CL40 CL36 11 0.0015 .994 . . 341 18.9 0.1558 22 CL31 CL42 6 0.0009 .993 . . 316 9.8 0.1614 21 CL29 CL44 9 0.0012 .992 . . 291 10.4 0.1756 20 CL23 CL54 13 0.0014 .990 . . 268 6.8 0.1873 19 CL27 CL33 12 0.0025 .988 . . 228 20.2 0.1921 18 CL22 Riverside 7 0.0008 .987 . . 232 2.9 0.1967 17 CL32 CL24 7 0.0019 .985 . . 218 13.7 0.2131 16 CL21 Miami 10 0.0013 .984 . . 219 5.1 0.2356 15 CL26 CL17 10 0.0028 .981 . . 203 7.5 0.25 14 CL19 CL63 14 0.0028 .978 .975 1.29 194 8.8 0.2593 13 Dallas/Fort Worth Las Vegas 2 0.0011 .977 .972 1.82 203 . 0.2811

18:24 Saturday, November 21, 2009 136 Clustering based on First two Temperature PCs

Page 74: R Code for Calculating Beale’s F-Type Statistic: c1

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

12 CL48 CL18 9 0.0039 .973 .968 1.49 192 12.7 0.3105 11 CL68 Tacoma 3 0.0019 .971 .964 1.97 200 . 0.3156 10 CL20 CL25 17 0.0102 .961 .959 0.46 165 39.3 0.3573 9 CL15 CL10 27 0.0212 .940 .953 -2.1 119 26.7 0.4058 8 CL16 CL13 12 0.0092 .931 .945 -2.1 119 21.0 0.4696 7 CL12 CL8 21 0.0265 .904 .935 -3.5 99.1 25.8 0.4897 6 CL14 CL67 16 0.0140 .890 .921 -3.1 104 29.7 0.5402 5 CL6 CL9 43 0.0842 .806 .902 -6.5 67.5 56.0 0.6213 4 CL28 CL11 5 0.0170 .789 .874 -5.0 82.3 24.1 0.7161 3 CL7 Phoenix 22 0.0155 .774 .825 -1.9 114 6.7 0.7964 2 CL5 CL4 48 0.1240 .650 .695 -1.3 126 34.6 1.0972 1 CL2 CL3 70 0.6496 .000 .000 0.00 . 126 1.3378

18:24 Saturday, November 21, 2009 137 Clustering based on First two Temperature PCs

Plot of _CCC_*_NCL_. Symbol is value of _NCL_.

‚ ‚ 2 ˆ 1 ‚ 1 ‚ 1 1 ‚ C ‚ u ‚ 1 b ‚ i 0 ˆ 1 c ‚ ‚ C ‚ l ‚ 2 u ‚ s ‚ t -2 ˆ 3 89 e ‚ r ‚ i ‚ n ‚ 6 g ‚ 7 ‚ C -4 ˆ r ‚ i ‚ t ‚ e ‚ 4 r ‚ i ‚

Page 75: R Code for Calculating Beale’s F-Type Statistic: c1

o -6 ˆ n ‚ ‚ 5 ‚ ‚ ‚ ‚ -8 ˆ ‚ Šƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒ 0 10 20 30 40 50 60 70

Number of Clusters

NOTE: 125 obs had missing values.

18:24 Saturday, November 21, 2009 138 Clustering based on First two Temperature PCs 6 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=4 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -28.99302565 2.11735872 2 -10.70761073 -8.80120169 3 7.10205831 2.54042760 4 31.80245481 9.14494722

Criterion Based on Final Seeds = 4.9597

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 10 6.6024 15.7266 2 14.1879 2 24 4.0985 9.6044 3 13.2925 3 20 4.4703 9.4856 2 13.2925 4 16 4.4878 12.6290 3 17.6139

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCT1 15.50960 4.79223 0.908679 9.950427 PCT2 4.70672 4.61424 0.080696 0.087779 OVER-ALL 11.46082 4.70408 0.838857 5.205656

Pseudo F Statistic = 114.52

Approximate Expected Over-All R-Squared = 0.87366

Cubic Clustering Criterion = -2.390

WARNING: The two values above are invalid for correlated variables.

18:24 Saturday, November 21, 2009 139 Clustering based on First two Temperature PCs

Page 76: R Code for Calculating Beale’s F-Type Statistic: c1

6 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=4 Maxiter=1

Cluster Means

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -22.63592343 -2.28701890 2 -8.86349998 1.12121166 3 4.42595184 0.83555914 4 21.91026232 -1.29687960

Cluster Standard Deviations

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 5.403296513 7.614931949 2 3.964806246 4.227986793 3 5.780142003 2.560834497 4 4.136150227 4.813808736

18:24 Saturday, November 21, 2009 140 Clustering based on First two Temperature PCs 6 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 3443.82 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 141 Clustering based on First two Temperature PCs 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -1.48244429 -3.37764387 2 4.05087904 3.28666006 3 31.80245481 9.14494722 4 26.17447188 -7.17847001 5 16.77777720 -1.25650104 6 20.76507818 8.92838212 7 -28.99302565 2.11735872 8 -17.13076388 2.98732592 9 -10.70761073 -8.80120169 10 -25.24870940 -14.59398355 11 -5.76840458 4.47692301

Criterion Based on Final Seeds = 2.0521

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between

Page 77: R Code for Calculating Beale’s F-Type Statistic: c1

Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 7 2.2972 3.6943 2 7.6959 2 9 2.6961 5.2824 1 7.6959 3 1 . 0 6 11.0395 4 9 1.5927 3.6463 5 8.5441 5 9 2.6755 5.8194 4 8.5441 6 1 . 0 5 10.3820 7 2 1.3076 1.3076 8 12.4384 8 12 1.7656 3.8435 11 9.6042 9 2 0 0 1 10.7848 10 3 2.9535 4.8230 7 16.0024 11 15 2.1747 5.2756 1 7.7135

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCT1 15.50960 2.52006 0.977425 43.297218 PCT2 4.70672 1.83825 0.869571 6.667016 OVER-ALL 11.46082 2.20566 0.968330 30.575663

18:24 Saturday, November 21, 2009 142 Clustering based on First two Temperature PCs 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Pseudo F Statistic = 180.40

Approximate Expected Over-All R-Squared = 0.96404

Cubic Clustering Criterion = 1.109

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -1.78476234 -2.74352281 2 4.83676492 1.17853666 3 31.80245481 9.14494722 4 23.30670087 -4.13857205 5 15.74570435 -0.15957217 6 20.76507818 8.92838212 7 -27.90943209 2.84922500 8 -15.49449227 2.08637051 9 -10.70761073 -8.80120169 10 -27.16955932 -13.13602015 11 -6.02667046 3.69889107

Cluster Standard Deviations

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 2.444285502 2.140040512 2 2.795242812 2.593223408 3 . . 4 1.642922651 1.540860056 5 2.969514394 2.344903825 6 . . 7 1.532432705 1.035015216

Page 78: R Code for Calculating Beale’s F-Type Statistic: c1

8 2.248937663 1.084852191 9 0.000000000 0.000000000 10 3.327009663 2.525266688 11 2.726564437 1.422741638

18:24 Saturday, November 21, 2009 143 Clustering based on First two Temperature PCs 11 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 589.5693873 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 144 Clustering based on First two Temperature PCs 13 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=13 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -10.70761073 -8.80120169 2 -0.92288883 5.03435131 3 7.84308181 -3.00296132 4 15.69438709 3.21336035 5 -25.24870940 -14.59398355 6 18.87002003 -3.81007102 7 26.17447188 -7.17847001 8 -18.43210136 1.22793573 9 20.76507818 8.92838212 10 31.80245481 9.14494722 11 -7.86891703 2.60659500 12 -3.25721263 -4.40197237 13 -28.99302565 2.11735872

Criterion Based on Final Seeds = 1.8781

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 2 0 0 12 10.5786 2 7 2.2024 4.1056 11 6.2334 3 6 2.2135 4.4945 2 7.5822 4 6 1.7307 3.8344 6 5.5907 5 3 2.9535 4.8230 13 16.0024 6 4 2.5369 5.9056 7 5.0628 7 8 1.4719 3.1787 6 5.0628 8 12 1.7656 3.8338 11 8.7290 9 1 . 0 6 10.5156 10 1 . 0 9 11.0395 11 12 1.8439 3.9518 2 6.2334 12 6 2.1772 3.7456 2 6.3401 13 2 1.3076 1.3076 8 12.4384

Page 79: R Code for Calculating Beale’s F-Type Statistic: c1

18:24 Saturday, November 21, 2009 145 Clustering based on First two Temperature PCs 13 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=13 Maxiter=1

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCT1 15.50960 2.10732 0.984749 64.571141 PCT2 4.70672 1.78724 0.880889 7.395497 OVER-ALL 11.46082 1.95385 0.975991 40.650961

Pseudo F Statistic = 193.09

Approximate Expected Over-All R-Squared = 0.97173

Cubic Clustering Criterion = 1.413

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -10.70761073 -8.80120169 2 -0.72337074 2.92934854 3 6.41921208 0.38507971 4 14.07443988 0.18143341 5 -27.16955932 -13.13602015 6 19.40662567 -1.49905884 7 23.67481312 -4.22195788 8 -15.49449227 2.08637051 9 20.76507818 8.92838212 10 31.80245481 9.14494722 11 -6.91168465 3.67746207 12 -1.64566175 -3.34332109 13 -27.90943209 2.84922500

18:24 Saturday, November 21, 2009 146 Clustering based on First two Temperature PCs 13 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=13 Maxiter=1

Cluster Standard Deviations

Cluster PCT1 PCT2 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 0.000000000 0.000000000 2 2.421674916 1.958795366 3 1.801270875 2.560110617 4 1.302910943 2.071905260 5 3.327009663 2.525266688 6 2.081383950 2.922259210 7 1.300389031 1.625395227 8 2.248937663 1.084852191 9 . . 10 . . 11 2.199983009 1.400064525 12 2.647056206 1.572819464

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13 1.532432705 1.035015216

18:24 Saturday, November 21, 2009 147 Clustering based on First two Temperature PCs 13 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 493.7919436 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 148 Cities in their Clusters

Obs city PCT1 PCT2 CLUSTER CLUSNAME

1 Kingston -5.7684 4.4769 1 CL20 2 New York -5.7684 4.4769 1 CL20 3 Cincinnati -6.7571 1.6912 1 CL20 4 Indianapolis -6.1580 2.0379 1 CL20 5 Jersey City -4.3017 4.8683 1 CL20 6 Philadelphia -3.5652 4.6440 1 CL20 7 Kansas CityMO -5.9731 3.7010 1 CL20 8 Evansville -2.6194 0.8553 1 CL20 9 Lexington -2.9717 1.6754 1 CL20 10 Dayton -8.4739 1.8203 1 CL20 11 Washington -7.8689 2.6066 1 CL20 12 Kansas CityKS -5.1993 5.5430 1 CL20 13 ColumbusOH -4.8662 2.9176 1 CL20 14 Oakland -25.2487 -14.5940 2 CL68 15 San Jose -25.2487 -14.5940 2 CL68 16 Los Angeles -10.7076 -8.8012 3 CL67 17 Santa Ana/Anaheim -10.7076 -8.8012 3 CL67 18 St. Petersburg 23.7667 -4.8977 4 CL16 19 Tampa 23.7667 -4.8977 4 CL16 20 Corpus Christi 24.2833 -4.9156 4 CL16 21 Houston 22.8477 -2.9608 4 CL16 22 San Antonio 22.3267 -2.4535 4 CL16 23 Baton Rouge 18.8700 -3.8101 4 CL16 24 Lake Charles 20.3618 -3.4715 4 CL16 25 Lafayette 22.0975 -4.1566 4 CL16 26 Austin 24.1355 -2.3152 4 CL16 27 Miami 26.1745 -7.1785 4 CL16 28 Johnstown -16.7821 2.8679 5 CL14 29 Syracuse -17.1308 2.9873 5 CL14 30 Lincoln -10.9795 5.2255 5 CL14 31 Omaha -10.8258 4.7645 5 CL14 32 Fort Wayne -12.3593 2.8851 5 CL14 33 Toledo -12.7102 2.2801 5 CL14 34 Akron -14.9869 0.6743 5 CL14 35 Pittsburgh -14.3237 0.2579 5 CL14 36 Grand Rapids -17.3701 1.2652 5 CL14 37 Worcester -18.4321 1.2279 5 CL14 38 Boston -14.1691 2.6226 5 CL14 39 Cleveland -14.4028 1.5558 5 CL14 40 Buffalo -19.3166 2.4911 5 CL14 41 Chicago -13.9503 3.9212 5 CL14 42 Charlotte 1.6325 -1.6437 6 CL15 43 Knoxville 1.4423 -1.2235 6 CL15 44 Fresno 4.9179 1.2236 6 CL15 45 Nashville 5.8323 0.6114 6 CL15 46 Arlington 1.5472 4.8813 6 CL15 47 St. Louis 0.9640 2.9282 6 CL15 48 Bakersfield 2.5044 0.4868 6 CL15

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49 Oklahoma City 7.1021 2.5404 6 CL15 50 Wichita -0.9229 5.0344 6 CL15

18:24 Saturday, November 21, 2009 149 Cities in their Clusters

Obs city PCT1 PCT2 CLUSTER CLUSNAME

51 Louisville 4.0509 3.2867 6 CL15 52 Sacramento -4.2394 -4.9783 7 CL25 53 Stockton -3.9697 -4.4348 7 CL25 54 Modesto -3.2572 -4.4020 7 CL25 55 San Bernardino -1.4824 -3.3776 7 CL25 56 Atlanta 7.8431 -3.0030 8 CL48 57 Huntsville 8.7691 -2.3486 8 CL48 58 ColumbusGA 14.0706 -1.9498 9 CL18 59 Jackson 15.2773 -2.2649 9 CL18 60 El Paso 12.1305 0.5803 9 CL18 61 Little Rock 13.2797 1.4361 9 CL18 62 Memphis 13.9942 0.0735 9 CL18 63 Shreveport 16.7778 -1.2565 9 CL18 64 Riverside 15.6944 3.2134 9 CL18 65 Colorado Springs -28.9930 2.1174 10 CL28 66 Denver -26.8258 3.5811 10 CL28 67 Dallas/Fort Worth 21.6169 2.5418 11 CL13 68 Las Vegas 20.7651 8.9284 11 CL13 69 Tacoma -31.0113 -10.2201 12 Tacoma 70 Phoenix 31.8025 9.1449 13 Phoenix

18:24 Saturday, November 21, 2009 150 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Eigenvalues of the Covariance Matrix

Eigenvalue Difference Proportion Cumulative

1 91.4204695 34.1181979 0.4794 0.4794 2 57.3022716 27.7307075 0.3005 0.7799 3 29.5715640 17.1594150 0.1551 0.9349 4 12.4121490 0.0651 1.0000

Root-Mean-Square Total-Sample Standard Deviation = 6.904825 Root-Mean-Square Distance Between Observations = 19.5298

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

69 St. Petersburg Tampa 2 0.0000 1.00 . . 388 . 0.0511 68 Cleveland Dayton 2 0.0001 1.00 . . 252 . 0.0745 67 Oakland San Jose 2 0.0002 1.00 . . 165 . 0.104 66 Akron CL68 3 0.0004 .999 . . 88.0 5.3 0.1527 65 Kansas CityKS San Bernardino 2 0.0003 .999 . . 74.6 . 0.1549 64 Kansas CityMO St. Louis 2 0.0003 .999 . . 68.2 . 0.1551 63 Atlanta Memphis 2 0.0004 .998 . . 63.7 . 0.1606

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62 Denver Phoenix 2 0.0004 .998 . . 60.6 . 0.1639 61 CL64 Louisville 3 0.0004 .997 . . 58.3 1.2 0.1648 60 Sacramento Stockton 2 0.0004 .997 . . 56.2 . 0.1742 59 Johnstown Worcester 2 0.0005 .997 . . 54.2 . 0.1822 58 El Paso Los Angeles 2 0.0006 .996 . . 51.7 . 0.1979 57 CL67 Tacoma 3 0.0008 .995 . . 47.2 5.4 0.2153 56 CL66 ColumbusOH 4 0.0009 .994 . . 43.6 3.6 0.2179

18:24 Saturday, November 21, 2009 151 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

55 Buffalo Syracuse 2 0.0007 .993 . . 42.4 . 0.2197 54 Oklahoma City Wichita 2 0.0007 .993 . . 41.4 . 0.2264 53 Arlington New York 2 0.0008 .992 . . 40.2 . 0.2371 52 Little Rock Shreveport 2 0.0008 .991 . . 39.4 . 0.2385 51 Modesto Riverside 2 0.0008 .990 . . 38.7 . 0.2407 50 Fort Wayne Indianapolis 2 0.0009 .989 . . 38.2 . 0.2433 49 Baton Rouge Lafayette 2 0.0009 .988 . . 37.6 . 0.2516 48 Bakersfield Fresno 2 0.0009 .988 . . 37.2 . 0.2537 47 CL62 CL65 4 0.0016 .986 . . 35.1 4.4 0.2624 46 Boston Colorado Springs 2 0.0011 .985 . . 34.6 . 0.2765 45 Houston San Antonio 2 0.0012 .984 . . 34.1 . 0.2909 44 CL58 Santa Ana/Anaheim 3 0.0015 .982 . . 33.2 2.6 0.294 43 Cincinnati CL61 4 0.0017 .980 . . 32.2 4.6 0.2969 42 CL56 Toledo 5 0.0019 .979 . . 31.1 4.0 0.3056 41 CL44 CL60 5 0.0023 .976 . . 29.7 2.8 0.3133 40 ColumbusGA Jackson 2 0.0014 .975 . . 29.7 . 0.3155 39 CL55 Pittsburgh 3 0.0017 .973 . . 29.4 2.4 0.3174 38 Jersey City Philadelphia 2 0.0016 .971 . . 29.4 . 0.3344 37 CL57 CL69 5 0.0036 .968 . . 27.6 10.3 0.3382 36 Evansville Lexington 2 0.0017 .966 . . 27.8 . 0.3391 35 CL47 Las Vegas 5 0.0026 .964 . . 27.2 3.3 0.3656

Page 83: R Code for Calculating Beale’s F-Type Statistic: c1

18:24 Saturday, November 21, 2009 152 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

34 CL35 CL51 7 0.0037 .960 . . 26.1 3.1 0.3709 33 CL46 Kingston 3 0.0023 .958 . . 26.1 2.1 0.374 32 CL45 Lake Charles 3 0.0023 .955 . . 26.2 1.9 0.3741 31 Dallas/Fort Worth CL52 3 0.0025 .953 . . 26.2 3.1 0.3817 30 Huntsville Nashville 2 0.0022 .951 . . 26.5 . 0.387 29 Austin CL32 4 0.0024 .948 . . 26.8 1.4 0.3877 28 CL43 Knoxville 5 0.0030 .945 . . 26.8 3.7 0.3898 27 Chicago CL59 3 0.0028 .942 . . 27.0 5.8 0.3906 26 CL63 CL40 4 0.0037 .939 . . 26.9 4.1 0.3981 25 CL50 Grand Rapids 3 0.0029 .936 . . 27.3 3.4 0.4045 24 CL33 CL27 6 0.0039 .932 . . 27.4 2.3 0.4087 23 CL34 CL41 12 0.0090 .923 . . 25.6 6.3 0.4322 22 CL38 Washington 3 0.0031 .920 . . 26.2 1.9 0.4336 21 CL42 CL25 8 0.0069 .913 . . 25.7 5.9 0.438 20 CL30 CL54 4 0.0042 .909 . . 26.2 2.9 0.4401 19 CL28 CL36 7 0.0053 .903 . . 26.5 3.7 0.4424 18 Lincoln CL37 6 0.0040 .899 . . 27.4 3.5 0.4438 17 CL31 CL20 7 0.0072 .892 . . 27.4 3.4 0.4935 16 CL29 CL49 6 0.0086 .884 . . 27.4 5.0 0.5371 15 Charlotte CL19 8 0.0060 .878 . . 28.2 2.9 0.5468 14 Corpus Christi Miami 2 0.0046 .873 .863 1.10 29.6 . 0.563

18:24 Saturday, November 21, 2009 153 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

13 CL21 CL53 10 0.0126 .860 .852

Page 84: R Code for Calculating Beale’s F-Type Statistic: c1

0.80 29.3 6.9 0.5884 12 CL24 CL39 9 0.0166 .844 .841 0.27 28.5 8.9 0.6127 11 CL15 Omaha 9 0.0076 .836 .828 0.73 30.1 2.9 0.6133 10 CL13 CL12 19 0.0287 .807 .813 -.46 28.0 8.6 0.6459 9 CL26 CL11 13 0.0258 .782 .796 -.94 27.3 9.0 0.6852 8 CL23 CL22 15 0.0303 .751 .777 -1.5 26.8 14.0 0.7463 7 CL14 CL18 8 0.0215 .730 .753 -1.3 28.4 9.8 0.7887 6 CL16 CL7 14 0.0418 .688 .723 -1.8 28.2 10.0 0.8114 5 CL17 CL8 22 0.0673 .621 .684 -3.0 26.6 17.7 0.8411 4 CL10 CL9 32 0.0980 .523 .632 -4.6 24.1 20.5 0.8639 3 CL48 CL5 24 0.0323 .490 .551 -2.1 32.2 4.9 0.9213 2 CL4 CL3 56 0.2073 .283 .374 -2.6 26.9 26.8 1.0175 1 CL2 CL6 70 0.2831 .000 .000 0.00 . 26.9 1.218

18:24 Saturday, November 21, 2009 154 Clustering based on Monthly Average Temperature and Ozone

Plot of _CCC_*_NCL_. Symbol is value of _NCL_.

‚ 2 ˆ ‚ ‚ ‚ ‚ ‚ 1 1 ˆ ‚ 1 C ‚ 1 u ‚ b ‚ 1 i ‚ c 0 ˆ 1 ‚ C ‚ l ‚ 1 u ‚ s ‚ t -1 ˆ 9 e ‚ r ‚ 7 i ‚ 8 n ‚ g ‚ 6 -2 ˆ C ‚ 3 r ‚ i ‚ t ‚ 2 e ‚ r -3 ˆ 5 i ‚ o ‚ n ‚ ‚ ‚ -4 ˆ

Page 85: R Code for Calculating Beale’s F-Type Statistic: c1

‚ ‚ ‚ ‚ 4 ‚ -5 ˆ Šƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒ 0 10 20 30 40 50 60 70

Number of Clusters

NOTE: 125 obs had missing values.

18:24 Saturday, November 21, 2009 155 Clustering based on Monthly Average Temperature and Ozone 3 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=3 Maxiter=1

Initial Seeds

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.47086690 -16.90830816 0.47613678 -0.44864696 2 -20.74774458 9.36293579 -1.92570126 2.55375831 3 13.82101526 12.50743969 4.47700609 9.17367551

Criterion Based on Final Seeds = 4.7510

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 29 4.5063 13.4106 3 14.7904 2 19 5.5477 18.8948 1 17.5661 3 22 4.6497 14.1085 1 14.7904

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCO1 9.56141 5.69407 0.655628 1.903833 PCO2 7.56983 4.75413 0.617002 1.610982 PCO3 5.43797 5.13406 0.134486 0.155383 PCO4 3.52309 3.56941 0.003281 0.003292 OVER-ALL 6.90483 4.85087 0.520754 1.086610

Pseudo F Statistic = 36.40

Approximate Expected Over-All R-Squared = 0.55068

Cubic Clustering Criterion = -1.102

WARNING: The two values above are invalid for correlated variables.

18:24 Saturday, November 21, 2009 156 Clustering based on Monthly Average Temperature and Ozone 3 Clusters, NH method

Page 86: R Code for Calculating Beale’s F-Type Statistic: c1

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=3 Maxiter=1

Cluster Means

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 2.52934352 -6.80822598 -1.36379318 0.06427548 2 -12.17424022 2.79509062 -1.30450328 -0.31672371 3 7.17998192 6.56053780 2.92434384 0.18880735

Cluster Standard Deviations

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 5.201439311 3.904577754 5.318259590 3.262226081 2 6.498660672 6.044588685 6.127024911 2.606909878 3 5.583049748 4.523855294 3.769243568 4.542504510

18:24 Saturday, November 21, 2009 157 Clustering based on Monthly Average Temperature and Ozone 3 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 6320.20 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 158 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=7 Maxiter=1

Initial Seeds

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.47086690 -16.90830816 0.47613678 -0.44864696 2 17.62711647 0.88212599 -0.58601647 -2.65441445 3 -11.44422976 2.81056112 -7.90445907 -2.17044852 4 1.52543058 15.88510614 -3.98916959 -4.60274869 5 10.95847761 12.37348243 2.11023068 12.44931239 6 -22.67064748 -9.53709355 7.08928951 -3.23676902 7 0.69294273 2.31650915 5.60732222 2.52557376

Criterion Based on Final Seeds = 3.8438

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 15 3.4459 11.3124 7 13.6328 2 10 4.2811 10.5994 7 11.5030 3 14 4.7529 14.1964 4 12.8179 4 5 2.6444 5.5282 3 12.8179 5 2 1.7516 2.4771 2 16.6073

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6 7 4.1232 10.3505 3 14.5622 7 17 3.7709 11.4221 2 11.5030

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCO1 9.56141 4.62682 0.786197 3.677199 PCO2 7.56983 4.34278 0.699493 2.327707 PCO3 5.43797 3.59701 0.600515 1.503225 PCO4 3.52309 3.05951 0.311429 0.452282 OVER-ALL 6.90483 3.95494 0.700452 2.338361

Pseudo F Statistic = 24.55

Approximate Expected Over-All R-Squared = 0.75268

18:24 Saturday, November 21, 2009 159 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=7 Maxiter=1

Cubic Clustering Criterion = -2.756

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 2.84397806 -9.53534110 -2.41821342 0.48466906 2 12.48137463 0.64423392 -0.03406928 -0.39434054 3 -7.73331730 2.61289128 -5.02796250 -0.32401842 4 -0.96230978 13.40910737 -4.80312556 -1.68161474 5 12.38974643 12.44046106 3.29361838 10.81149395 6 -17.05517812 -2.69532263 4.80065288 0.29501831 7 2.36537223 1.58518229 5.34289353 -0.82767147

Cluster Standard Deviations

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.075603834 3.359063089 3.591456936 2.589242636 2 3.141533633 5.779486817 4.736585299 2.757880052 3 6.362183875 4.079347641 4.398117806 3.728212400 4 2.962695791 2.191393654 2.201513909 3.089334743 5 2.024119787 0.094722089 1.673562940 2.316225053 6 5.384034254 4.534083909 2.648019271 3.382987673 7 4.242361014 4.813229684 2.703036672 2.899401819

18:24 Saturday, November 21, 2009 160 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 4136.98

Page 88: R Code for Calculating Beale’s F-Type Statistic: c1

ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 161 Clustering based on Monthly Average Temperature and Ozone 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Initial Seeds

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.47086690 -16.90830816 0.47613678 -0.44864696 2 -2.47944102 -7.31440494 -9.72389792 4.00458550 3 1.52543058 15.88510614 -3.98916959 -4.60274869 4 -20.74774458 9.36293579 -1.92570126 2.55375831 5 10.95847761 12.37348243 2.11023068 12.44931239 6 -8.70793720 6.34263287 1.28387081 -2.44534488 7 -0.73428048 -6.26858594 8.18331923 -1.13214014 8 17.61728069 9.43806143 -2.92259233 -1.80934960 9 1.02427673 -0.38896807 -8.45618803 -8.14182229 10 -22.67064748 -9.53709355 7.08928951 -3.23676902 11 6.01546199 5.37368726 3.75060905 -4.85953725

Criterion Based on Final Seeds = 2.9235

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 11 3.0571 9.3685 2 9.5064 2 6 3.0179 8.3019 9 8.3569 3 5 2.6444 5.5282 6 12.2280 4 4 2.5455 4.8528 10 12.2204 5 2 1.7516 2.4771 11 15.1732 6 8 3.4461 9.5181 3 12.2280 7 9 3.3251 8.3565 2 10.9030 8 3 2.7842 5.2081 11 12.4154 9 4 3.5552 9.3990 2 8.3569 10 4 3.7335 7.7465 4 12.2204 11 14 2.9945 10.8409 8 12.4154

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCO1 9.56141 3.69088 0.872585 6.848387 PCO2 7.56983 2.99439 0.866202 6.473980 PCO3 5.43797 2.91456 0.754373 3.071219 PCO4 3.52309 2.78476 0.465765 0.871836 OVER-ALL 6.90483 3.11603 0.825859 4.742478

18:24 Saturday, November 21, 2009 162 Clustering based on Monthly Average Temperature and Ozone 11 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=11 Maxiter=1

Pseudo F Statistic = 27.98

Approximate Expected Over-All R-Squared = 0.82791

Page 89: R Code for Calculating Beale’s F-Type Statistic: c1

Cubic Clustering Criterion = -0.176

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 7.07383203 -9.34134391 -1.80262162 1.11823967 2 -1.43330571 -6.65303140 -4.91109013 2.17179398 3 -0.96230978 13.40910737 -4.80312556 -1.68161474 4 -18.69669877 5.50237011 0.15441716 2.21866066 5 12.38974643 12.44046106 3.29361838 10.81149395 6 -8.38977621 3.71852383 -5.29950407 -1.23041433 7 -2.06872113 -5.57519460 5.21821190 -1.66330223 8 16.59424712 5.21250871 -0.30784348 -2.98640689 9 3.39292549 -2.67161604 -7.93845830 -2.46814563 10 -18.02539876 -4.66355725 6.35012675 -0.45634479 11 5.72074176 4.49062570 4.91536308 -0.13933857

Cluster Standard Deviations

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 2.893172583 3.958920669 2.941973115 2.164347285 2 2.299494070 3.266873517 2.629878590 3.681802171 3 2.962695791 2.191393654 2.201513909 3.089334743 4 2.946096069 3.183263103 2.052113596 1.701158164 5 2.024119787 0.094722089 1.673562940 2.316225053 6 3.476586897 2.334811494 5.029578315 2.160489928 7 5.095903372 2.521901730 2.742625447 2.091537363 8 1.780470941 4.278930920 2.764352418 1.373483514 9 4.554554997 2.125639791 2.369217393 4.436574354 10 5.363176134 3.261352302 1.041538456 3.908011016 11 3.732698281 2.748202273 2.363208564 2.966268669

18:24 Saturday, November 21, 2009 163 Clustering based on Monthly Average Temperature and Ozone 11 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 2393.05 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 164 Clustering based on Monthly Average Temperature and Ozone 15 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=15 Maxiter=1

Initial Seeds

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -22.66652374 -3.02164952 4.85089941 5.33374256 2 10.20747823 -5.34320472 -9.32655058 -2.83482547 3 -22.67064748 -9.53709355 7.08928951 -3.23676902 4 -20.74774458 9.36293579 -1.92570126 2.55375831

Page 90: R Code for Calculating Beale’s F-Type Statistic: c1

5 10.95847761 12.37348243 2.11023068 12.44931239 6 -8.70793720 6.34263287 1.28387081 -2.44534488 7 2.46756897 7.36839188 8.35769514 -0.32727043 8 9.88540526 -4.15693670 3.30173918 4.47144343 9 1.02427673 -0.38896807 -8.45618803 -8.14182229 10 -6.70417273 -5.44491369 8.18469507 -1.98514609 11 4.47086690 -16.90830816 0.47613678 -0.44864696 12 1.52543058 15.88510614 -3.98916959 -4.60274869 13 17.61728069 9.43806143 -2.92259233 -1.80934960 14 -12.53842840 1.94963998 -7.87801441 3.83149139 15 -2.47944102 -7.31440494 -9.72389792 4.00458550

Criterion Based on Final Seeds = 2.4715

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 1 . 0 4 10.9626 2 6 2.4733 6.8679 11 7.9834 3 1 . 0 1 10.9961 4 4 2.5455 4.8528 1 10.9626 5 2 1.7516 2.4771 7 15.3329 6 4 2.9132 6.1180 14 8.8956 7 13 2.6604 6.1079 8 10.2385 8 5 3.0465 6.8723 2 8.2961 9 2 2.9239 4.1351 15 8.5762 10 8 3.0844 8.7202 6 12.1344 11 5 2.7361 5.9629 2 7.9834 12 5 2.6444 5.5282 6 11.6846 13 3 2.7842 5.2081 7 12.8646 14 4 2.4565 5.5913 6 8.8956 15 7 3.0656 8.3019 9 8.5762

18:24 Saturday, November 21, 2009 165 Clustering based on Monthly Average Temperature and Ozone 15 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=15 Maxiter=1

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCO1 9.56141 3.37235 0.900840 9.084720 PCO2 7.56983 2.56716 0.908326 9.908173 PCO3 5.43797 2.43799 0.839785 5.241595 PCO4 3.52309 2.62773 0.556567 1.255132 OVER-ALL 6.90483 2.77542 0.871215 6.764865

Pseudo F Statistic = 26.58

Approximate Expected Over-All R-Squared = .

Cubic Clustering Criterion = .

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Page 91: R Code for Calculating Beale’s F-Type Statistic: c1

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -22.66652374 -3.02164952 4.85089941 5.33374256 2 7.88395965 -7.85814683 -5.11345459 0.47142780 3 -22.67064748 -9.53709355 7.08928951 -3.23676902 4 -18.69669877 5.50237011 0.15441716 2.21866066 5 12.38974643 12.44046106 3.29361838 10.81149395 6 -7.69108129 4.61154248 -1.12988423 -2.28461912 7 5.13887854 5.04033517 4.92769142 -0.37283395 8 8.15892570 -4.17977099 2.24611064 1.49916044 9 1.29085711 -1.80914335 -6.45454177 -4.82455265 10 -6.92011057 -4.77893729 6.49914228 -1.76880067 11 4.63683566 -12.14931763 0.69619350 -0.54082484 12 -0.96230978 13.40910737 -4.80312556 -1.68161474 13 16.59424712 5.21250871 -0.30784348 -2.98640689 14 -9.08847114 2.82550518 -9.46912391 -0.17620954 15 -1.11676068 -5.94902302 -5.56924855 2.23458745

18:24 Saturday, November 21, 2009 166 Clustering based on Monthly Average Temperature and Ozone 15 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=15 Maxiter=1

Cluster Standard Deviations

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 . . . . 2 2.454817121 2.496458732 2.495119724 2.446337632 3 . . . . 4 2.946096069 3.183263103 2.052113596 1.701158164 5 2.024119787 0.094722089 1.673562940 2.316225053 6 3.932585551 3.146044705 2.842928239 0.708825285 7 3.155823720 1.897084473 2.459236831 2.950439104 8 4.782371815 1.134536469 2.004800748 2.991227265 9 0.377001589 2.008431143 2.830755287 4.691327724 10 5.178836874 2.395441127 2.056201886 1.125663140 11 1.841047912 3.412301888 2.676378506 2.783803747 12 2.962695791 2.191393654 2.201513909 3.089334743 13 1.780470941 4.278930920 2.764352418 1.373483514 14 3.381592872 0.834018918 2.140408564 2.724942527 15 2.260044128 3.516121931 2.965764442 3.365113741

18:24 Saturday, November 21, 2009 167 Clustering based on Monthly Average Temperature and Ozone 15 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 1710.36 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 168 Clustering based on Monthly Average Temperature and Ozone 17 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=17 Maxiter=1

Initial Seeds

Cluster PCO1 PCO2 PCO3 PCO4

Page 92: R Code for Calculating Beale’s F-Type Statistic: c1

ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 1.52543058 15.88510614 -3.98916959 -4.60274869 2 10.20747823 -5.34320472 -9.32655058 -2.83482547 3 1.48386155 4.77635995 4.61654050 4.50366152 4 -20.74774458 9.36293579 -1.92570126 2.55375831 5 10.95847761 12.37348243 2.11023068 12.44931239 6 -13.54687767 -2.70109629 7.02300182 -1.83322352 7 4.47086690 -16.90830816 0.47613678 -0.44864696 8 9.88540526 -4.15693670 3.30173918 4.47144343 9 1.02427673 -0.38896807 -8.45618803 -8.14182229 10 6.86169418 4.44840029 9.59601036 -2.92321872 11 -5.67936378 7.83580785 -3.67216244 -3.21430018 12 -22.67064748 -9.53709355 7.08928951 -3.23676902 13 -2.47944102 -7.31440494 -9.72389792 4.00458550 14 -12.53842840 1.94963998 -7.87801441 3.83149139 15 17.61728069 9.43806143 -2.92259233 -1.80934960 16 -22.66652374 -3.02164952 4.85089941 5.33374256 17 -0.73428048 -6.26858594 8.18331923 -1.13214014

Criterion Based on Final Seeds = 2.3527

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 5 2.6444 5.9448 11 10.2709 2 6 2.4733 6.8679 7 7.5824 3 6 2.2612 5.4501 10 5.8473 4 4 2.5455 4.8528 16 10.9626 5 2 1.7516 2.4771 3 14.9129 6 4 2.6120 6.8263 17 10.9797 7 4 2.5056 5.0458 2 7.5824 8 4 2.7305 6.5793 2 8.6733 9 2 2.9239 4.1351 13 8.5762 10 7 2.3005 5.4527 3 5.8473 11 3 2.6964 6.4348 14 8.6819 12 1 . 0 16 10.9961 13 7 3.0656 8.3019 9 8.5762 14 4 2.4565 5.1532 11 8.6819 15 3 2.7842 5.2081 10 10.8866 16 1 . 0 4 10.9626

18:24 Saturday, November 21, 2009 169 Clustering based on Monthly Average Temperature and Ozone 17 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=17 Maxiter=1

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 17 7 3.1951 7.0061 6 10.9797

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCO1 9.56141 2.96775 0.925999 12.513340 PCO2 7.56983 2.78198 0.896256 8.639137 PCO3 5.43797 2.52205 0.834781 5.052577

Page 93: R Code for Calculating Beale’s F-Type Statistic: c1

PCO4 3.52309 2.31250 0.669066 2.021750 OVER-ALL 6.90483 2.65779 0.886195 7.786965

Pseudo F Statistic = 25.79

Approximate Expected Over-All R-Squared = .

Cubic Clustering Criterion = .

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -0.96230978 13.40910737 -4.80312556 -1.68161474 2 7.88395965 -7.85814683 -5.11345459 0.47142780 3 2.97906143 5.30091883 5.12443761 1.89472710 4 -18.69669877 5.50237011 0.15441716 2.21866066 5 12.38974643 12.44046106 3.29361838 10.81149395 6 -12.16402506 -2.16026933 5.07591979 -1.78577945 7 4.84771526 -12.84627157 -0.27931047 0.31966457 8 9.36342443 -4.33884319 2.34584716 2.70981952 9 1.29085711 -1.80914335 -6.45454177 -4.82455265 10 6.99015035 4.81697774 4.75905184 -2.31645771 11 -6.01936028 4.96470924 -1.96606689 -2.43086751 12 -22.67064748 -9.53709355 7.08928951 -3.23676902 13 -1.11676068 -5.94902302 -5.56924855 2.23458745

18:24 Saturday, November 21, 2009 170 Clustering based on Monthly Average Temperature and Ozone 17 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=17 Maxiter=1

Cluster Means

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 14 -9.08847114 2.82550518 -9.46912391 -0.17620954 15 16.59424712 5.21250871 -0.30784348 -2.98640689 16 -22.66652374 -3.02164952 4.85089941 5.33374256 17 -1.75382580 -5.56333755 5.64478525 -2.31134569

Cluster Standard Deviations

Cluster PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 2.962695791 2.191393654 2.201513909 3.089334743 2 2.454817121 2.496458732 2.495119724 2.446337632 3 2.071430940 2.436551781 2.398261035 2.114925824 4 2.946096069 3.183263103 2.052113596 1.701158164 5 2.024119787 0.094722089 1.673562940 2.316225053 6 2.015622800 4.080395693 2.547245510 0.298168035 7 2.054947326 3.505249432 1.790702634 2.323030553 8 4.563185175 1.244000632 2.300576500 1.469223593 9 0.377001589 2.008431143 2.830755287 4.691327724 10 2.771198256 1.457542922 2.689006632 2.033134798 11 2.535731993 3.754735058 2.815697576 0.790770751 12 . . . . 13 2.260044128 3.516121931 2.965764442 3.365113741 14 3.381592872 0.834018918 2.140408564 2.724942527 15 1.780470941 4.278930920 2.764352418 1.373483514

Page 94: R Code for Calculating Beale’s F-Type Statistic: c1

16 . . . . 17 4.695246851 2.898645454 2.839964692 1.523632114

18:24 Saturday, November 21, 2009 171 Clustering based on Monthly Average Temperature and Ozone 17 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 1549.80 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 172 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Eigenvalues of the Covariance Matrix

Eigenvalue Difference Proportion Cumulative

1 285.029670 204.037162 0.6286 0.6286 2 80.992508 40.219962 0.1786 0.8073 3 40.772546 15.214273 0.0899 0.8972 4 25.558273 13.068800 0.0564 0.9536 5 12.489474 3.924713 0.0275 0.9811 6 8.564761 0.0189 1.0000

Root-Mean-Square Total-Sample Standard Deviation = 8.692978 Root-Mean-Square Distance Between Observations = 30.11336

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

69 St. Petersburg Tampa 2 0.0000 1.00 . . 922 . 0.0332 68 Oakland San Jose 2 0.0001 1.00 . . 364 . 0.0675 67 Akron Cleveland 2 0.0001 1.00 . . 228 . 0.0899 66 Sacramento Stockton 2 0.0002 1.00 . . 158 . 0.1147 65 Johnstown Worcester 2 0.0003 .999 . . 115 . 0.1412 64 Louisville St. Louis 2 0.0003 .999 . . 96.8 . 0.1448 63 Cincinnati Dayton 2 0.0004 .999 . . 83.4 . 0.1595 62 Buffalo Syracuse 2 0.0004 .998 . . 75.9 . 0.1607 61 ColumbusOH New York 2 0.0004 .998 . . 69.1 . 0.1746 60 Bakersfield Fresno 2 0.0005 .997 . . 63.5 . 0.1846 59 Los Angeles Santa Ana/Anaheim 2 0.0005 .997 . . 59.4 . 0.1899 58 Houston San Antonio 2 0.0005 .996 . . 56.6 . 0.1902

Page 95: R Code for Calculating Beale’s F-Type Statistic: c1

57 CL67 Toledo 3 0.0007 .996 . . 52.9 5.7 0.1907

18:24 Saturday, November 21, 2009 173 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

56 Baton Rouge Lafayette 2 0.0006 .995 . . 51.4 . 0.1956 55 Jackson Memphis 2 0.0006 .994 . . 49.9 . 0.2053 54 Boston Chicago 2 0.0006 .994 . . 48.6 . 0.2092 53 Modesto CL66 3 0.0008 .993 . . 46.6 4.1 0.21 52 Little Rock Shreveport 2 0.0007 .992 . . 46.0 . 0.2131 51 Jersey City Philadelphia 2 0.0007 .992 . . 45.4 . 0.2184 50 Evansville Lexington 2 0.0007 .991 . . 44.8 . 0.2219 49 CL63 Indianapolis 3 0.0009 .990 . . 43.7 2.4 0.2281 48 CL57 Fort Wayne 4 0.0010 .989 . . 42.3 2.7 0.2381 47 ColumbusGA CL55 3 0.0010 .988 . . 41.3 1.7 0.2528 46 Knoxville CL64 3 0.0011 .987 . . 40.1 3.7 0.2532 45 CL58 Lake Charles 3 0.0011 .986 . . 39.5 2.1 0.2552 44 CL62 Pittsburgh 3 0.0012 .985 . . 38.7 3.1 0.2595 43 CL49 Kansas CityMO 4 0.0012 .983 . . 38.1 2.0 0.2659 42 Austin CL45 4 0.0011 .982 . . 37.8 1.4 0.2663 41 CL54 CL65 4 0.0016 .981 . . 36.8 3.5 0.2674 40 CL68 Tacoma 3 0.0015 .979 . . 36.2 22.3 0.2779 39 Huntsville Nashville 2 0.0012 .978 . . 36.3 . 0.2866 38 Colorado Springs Denver 2 0.0012 .977 . . 36.4 . 0.2897 37 CL48 Grand Rapids 5 0.0017 .975 . . 35.8 2.9 0.3011 36 Arlington CL61 3 0.0018 .973 . . 35.4 4.0 0.3134

18:24 Saturday, November 21, 2009 174 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

Page 96: R Code for Calculating Beale’s F-Type Statistic: c1

35 Oklahoma City Wichita 2 0.0014 .972 . . 35.5 . 0.3153 34 CL51 Washington 3 0.0017 .970 . . 35.4 2.5 0.3184 33 Charlotte CL46 4 0.0020 .968 . . 35.2 2.7 0.3261 32 Atlanta CL47 4 0.0019 .966 . . 35.1 2.3 0.3272 31 CL53 San Bernardino 4 0.0021 .964 . . 34.9 4.4 0.3305 30 Kingston Lincoln 2 0.0016 .963 . . 35.4 . 0.334 29 Las Vegas Riverside 2 0.0017 .961 . . 35.9 . 0.3417 28 CL43 CL50 6 0.0033 .957 . . 35.0 4.2 0.3459 27 Dallas/Fort Worth CL52 3 0.0021 .955 . . 35.4 3.2 0.3481 26 CL34 Kansas CityKS 4 0.0022 .953 . . 35.8 1.8 0.361 25 CL37 CL41 9 0.0055 .948 . . 33.9 6.3 0.363 24 CL42 CL56 6 0.0038 .944 . . 33.6 4.6 0.3636 23 CL59 CL31 6 0.0038 .940 . . 33.5 4.2 0.3677 22 Corpus Christi Miami 2 0.0021 .938 . . 34.5 . 0.3781 21 CL39 CL35 4 0.0030 .935 . . 35.2 2.3 0.3862 20 CL22 CL69 4 0.0035 .931 . . 35.7 3.4 0.3963 19 El Paso CL29 3 0.0027 .929 . . 36.9 1.6 0.4105 18 CL25 CL44 12 0.0073 .921 . . 35.9 5.5 0.4166 17 CL28 Omaha 7 0.0035 .918 . . 37.0 2.7 0.4231 16 CL32 CL27 7 0.0074 .911 . . 36.6 5.8 0.4593 15 CL33 CL17 11 0.0104 .900 . . 35.4 7.0 0.469

18:24 Saturday, November 21, 2009 175 Clustering based on Monthly Average Temperature and Ozone

The CLUSTER Procedure Average Linkage Cluster Analysis

Cluster History NCL -----------Clusters Joined------------ FREQ SPRSQ RSQ ERSQ Norm T RMS i CCC PSF PST2 Dist e

14 CL36 CL15 14 0.0089 .891 .861 3.52 35.3 4.1 0.4798 13 CL24 CL20 10 0.0116 .880 .851 3.04 34.7 7.3 0.5061 12 CL18 CL30 14 0.0098 .870 .841 2.91 35.2 5.4 0.5334 11 CL26 CL23 10 0.0197 .850 .829 1.91 33.5 13.0 0.6049 10 CL19 Phoenix 4 0.0069 .843 .817 2.35 35.9 3.2 0.6069 9 CL12 CL14 28 0.0426 .801 .802 -.12 30.6 16.6 0.6119 8 CL16 CL21 11 0.0197 .781 .785

Page 97: R Code for Calculating Beale’s F-Type Statistic: c1

-.33 31.6 9.2 0.6195 7 CL60 CL11 12 0.0151 .766 .766 0.01 34.3 4.7 0.6565 6 CL38 CL40 5 0.0168 .749 .741 0.44 38.2 18.3 0.722 5 CL9 CL7 40 0.0713 .678 .710 -1.6 34.2 17.3 0.7509 4 CL8 CL10 15 0.0343 .643 .668 -1.2 39.7 8.9 0.7896 3 CL4 CL13 25 0.0831 .560 .604 -1.6 42.7 17.5 0.8699 2 CL5 CL6 45 0.0840 .476 .481 -.14 61.8 14.6 0.9919 1 CL2 CL3 70 0.4762 .000 .000 0.00 . 61.8 1.2417

18:24 Saturday, November 21, 2009 176 Clustering based on Monthly Average Temperature and Ozone

Plot of _CCC_*_NCL_. Symbol is value of _NCL_.

‚ 4 ˆ ‚ ‚ ‚ 1 ‚ ‚ ‚ 3 ˆ 1 C ‚ 1 u ‚ b ‚ i ‚ c ‚ 1 ‚ C 2 ˆ l ‚ 1 u ‚ s ‚ t ‚ e ‚ r ‚ i 1 ˆ n ‚ g ‚ ‚ C ‚ 6 r ‚ i ‚ t 0 ˆ 1 7 e ‚ 2 9 r ‚ 8 i ‚ o ‚ n ‚ ‚ -1 ˆ ‚ 4 ‚ ‚ ‚ 3 ‚ 5 ‚ -2 ˆ Šƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒˆƒƒ 0 10 20 30 40 50 60 70

Number of Clusters

Page 98: R Code for Calculating Beale’s F-Type Statistic: c1

NOTE: 125 obs had missing values.

18:24 Saturday, November 21, 2009 177 Clustering based on Monthly Average Temperature and Ozone 4 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=4 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -31.01125917 -10.22009334 -9.18543209 -6.09763360 5.46469736 -1.37489115 2 -7.86891703 2.60659500 17.61728069 9.43806143 -2.92259233 -1.80934960 3 31.80245481 9.14494722 6.01546199 5.37368726 3.75060905 -4.85953725 4 26.17447188 -7.17847001 -22.67064748 -9.53709355 7.08928951 -3.23676902

Criterion Based on Final Seeds = 5.2174

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 12 5.5526 17.8311 2 17.5462 2 34 5.4820 21.1966 1 17.5462 3 12 5.4127 18.6490 4 20.0149 4 12 4.1447 15.7688 3 20.0149

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCT1 15.50960 6.17489 0.848381 5.595493 PCT2 4.70672 4.35516 0.181031 0.221048 PCO1 9.56141 5.81890 0.645731 1.822716 PCO2 7.56983 6.07908 0.383122 0.621066 PCO3 5.43797 5.25498 0.106772 0.119535 PCO4 3.52309 3.45512 0.080027 0.086989 OVER-ALL 8.69298 5.28306 0.646712 1.830554

Pseudo F Statistic = 40.27

Approximate Expected Over-All R-Squared = 0.60808

Cubic Clustering Criterion = 1.928

WARNING: The two values above are invalid for correlated variables.

18:24 Saturday, November 21, 2009 178 Clustering based on Monthly Average Temperature and Ozone 4 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=4 Maxiter=1

Cluster Means

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ

Page 99: R Code for Calculating Beale’s F-Type Statistic: c1

1 -20.18231599 -1.30353686 0.48354999 -7.39947177 3.38307143 -1.10284303 2 -5.62934905 1.13094555 5.39201920 -0.81459922 -0.97827613 0.81488076 3 14.63395787 1.87184768 0.26283141 8.20665894 -1.68614211 -1.57424310 4 21.49818042 -3.77265655 -16.02376915 1.50084397 1.07485306 0.36825730

Cluster Standard Deviations

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 6.906015493 7.324488412 6.005657969 5.456048386 3.441848621 2.441823824 2 6.105267778 3.783909904 6.144693930 6.875219454 5.164466580 4.125980011 3 7.447101298 3.854530255 5.538411862 4.707878484 6.879426710 2.303293295 4 3.714916660 1.531389973 4.810791518 5.290850375 5.147891433 3.047697559

18:24 Saturday, November 21, 2009 179 Clustering based on Monthly Average Temperature and Ozone 4 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 11432.91 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 180 Clustering based on Monthly Average Temperature and Ozone 6 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=6 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 13.99418618 0.07354821 -6.20202551 2.59170848 -9.67136849 -1.50718189 2 -10.82576302 4.76445441 -5.35884936 -4.24289791 -2.13502111 7.51994881 3 31.80245481 9.14494722 6.01546199 5.37368726 3.75060905 -4.85953725 4 26.17447188 -7.17847001 -22.67064748 -9.53709355 7.08928951 -3.23676902 5 -7.86891703 2.60659500 17.61728069 9.43806143 -2.92259233 -1.80934960 6 -31.01125917 -10.22009334 -9.18543209 -6.09763360 5.46469736 -1.37489115

Criterion Based on Final Seeds = 4.4689

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 15 4.6937 16.8693 5 21.0409 2 23 3.9954 13.1130 5 15.9183 3 3 4.1332 10.0686 1 21.1088 4 9 3.6262 13.8299 1 21.4104 5 15 5.3097 17.2741 2 15.9183 6 5 5.0465 19.9474 2 22.8851

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ

Page 100: R Code for Calculating Beale’s F-Type Statistic: c1

PCT1 15.50960 5.42809 0.886388 7.801906 PCT2 4.70672 3.62458 0.449940 0.817984 PCO1 9.56141 5.10318 0.735778 2.784701 PCO2 7.56983 4.82438 0.623259 1.654346 PCO3 5.43797 4.25091 0.433213 0.764332 PCO4 3.52309 3.38669 0.142892 0.166714 OVER-ALL 8.69298 4.49923 0.751532 3.024659

Pseudo F Statistic = 38.72

Approximate Expected Over-All R-Squared = 0.69027

18:24 Saturday, November 21, 2009 181 Clustering based on Monthly Average Temperature and Ozone 6 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=6 Maxiter=1

Cubic Clustering Criterion = 3.517

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 10.84594210 -0.42865226 -3.70775989 6.01489111 -4.74546218 -1.53365754 2 -10.29628927 2.57026011 3.28644661 -7.74162600 -1.68380542 0.88689011 3 22.75397336 7.09556323 7.50822759 5.58344771 6.23973017 -2.24559934 4 23.30670087 -4.13857205 -17.73273716 0.76747707 3.04409326 0.57815439 5 -4.43794427 -0.20107529 8.74714012 5.20207681 2.05489707 1.11996897 6 -27.46550843 -6.74192209 -2.82180474 -2.77095152 6.59399425 -2.53194711

Cluster Standard Deviations

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 6.182223082 2.195744564 4.892030266 5.817820981 4.819220654 2.853212577 2 5.480553004 1.377956687 4.759108706 3.752306013 4.336468470 2.882568442 3 8.236154412 3.363829595 1.900388753 1.253164057 3.017640261 3.010497360 4 1.642922651 1.540860056 4.207946977 5.891985392 3.460164643 3.070447413 5 6.020309011 5.137052571 5.924057452 5.154839308 4.575388353 4.891375412 6 2.507151304 8.950682588 6.949559006 3.643019108 1.625025385 1.481654855

18:24 Saturday, November 21, 2009 182 Clustering based on Monthly Average Temperature and Ozone 6 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 8387.71 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 183 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=7 Maxiter=1

Page 101: R Code for Calculating Beale’s F-Type Statistic: c1

Initial Seeds

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -10.70761073 -8.80120169 2.46756897 7.36839188 8.35769514 -0.32727043 2 20.76507818 8.92838212 6.86169418 4.44840029 9.59601036 -2.92321872 3 -12.71018409 2.28009744 5.22705667 -11.18952550 -6.33433535 4.09184056 4 26.17447188 -7.17847001 -22.67064748 -9.53709355 7.08928951 -3.23676902 5 2.50439360 0.48683436 10.95847761 12.37348243 2.11023068 12.44931239 6 21.61690260 2.54182208 -4.73772104 15.18448813 -8.14898308 -0.28153788 7 -31.01125917 -10.22009334 -9.18543209 -6.09763360 5.46469736 -1.37489115

Criterion Based on Final Seeds = 4.1893

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 6 3.4340 14.3459 5 13.9276 2 4 4.4309 12.7349 6 19.9419 3 27 4.5168 17.1683 1 15.7092 4 9 3.6262 13.1614 6 18.4882 5 10 4.7478 15.0220 1 13.9276 6 9 3.7924 12.3759 4 18.4882 7 5 5.0465 19.9474 3 23.7482

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCT1 15.50960 5.59069 0.881363 7.429049 PCT2 4.70672 3.10454 0.602762 1.517381 PCO1 9.56141 4.95196 0.755092 3.083166 PCO2 7.56983 4.27468 0.708843 2.434576 PCO3 5.43797 3.97273 0.512702 1.052134 PCO4 3.52309 3.50303 0.097325 0.107819 OVER-ALL 8.69298 4.31553 0.774980 3.444042

Pseudo F Statistic = 36.16

18:24 Saturday, November 21, 2009 184 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=7 Maxiter=1

Approximate Expected Over-All R-Squared = 0.71779

Cubic Clustering Criterion = 3.982

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -5.23987876 -5.44015847 1.73378868 3.96861450 4.34465880 1.55014480 2 20.09811228 5.46673711 6.02340699 4.95906063 6.17520453 -2.49196720 3 -9.21854462 2.52337903 3.67394061 -7.01410809 -2.13035206 0.44541718

Page 102: R Code for Calculating Beale’s F-Type Statistic: c1

4 23.30670087 -4.13857205 -17.73273716 0.76747707 3.04409326 0.57815439 5 -0.29838069 2.41808660 9.89674353 8.75285733 0.29966444 0.16362200 6 14.49984104 -1.17570428 -6.55072596 7.23909773 -6.29030226 -0.61545978 7 -27.46550843 -6.74192209 -2.82180474 -2.77095152 6.59399425 -2.53194711

Cluster Standard Deviations

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4.711450904 2.921492576 3.337512459 2.384933998 4.099134951 2.528419894 2 8.569551835 4.260969897 3.350585095 1.614429824 2.467270300 2.506960588 3 6.791434443 1.585165858 5.056653082 3.943071421 4.685132295 3.271878387 4 1.642922651 1.540860056 4.207946977 5.891985392 3.460164643 3.070447413 5 5.134192293 2.781488416 6.104534677 4.496610059 2.948674246 5.913635689 6 4.396409998 2.110941436 3.880516206 4.973735433 4.133929182 2.371422316 7 2.507151304 8.950682588 6.949559006 3.643019108 1.625025385 1.481654855

18:24 Saturday, November 21, 2009 185 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 7371.11 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 186 Clustering based on Monthly Average Temperature and Ozone 10 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=10 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -28.99302565 2.11735872 0.82753041 -1.62598581 6.13963538 -4.20728037 2 21.61690260 2.54182208 -4.73772104 15.18448813 -8.14898308 -0.28153788 3 -25.24870940 -14.59398355 -6.70417273 -5.44491369 8.18469507 -1.98514609 4 -4.30168153 4.86827149 17.62711647 0.88212599 -0.58601647 -2.65441445 5 2.50439360 0.48683436 10.95847761 12.37348243 2.11023068 12.44931239 6 20.76507818 8.92838212 6.86169418 4.44840029 9.59601036 -2.92321872 7 26.17447188 -7.17847001 -22.67064748 -9.53709355 7.08928951 -3.23676902 8 -10.70761073 -8.80120169 2.46756897 7.36839188 8.35769514 -0.32727043 9 1.63252491 -1.64373523 1.02427673 -0.38896807 -8.45618803 -8.14182229 10 -10.97946361 5.22546624 -6.11627726 -9.05656062 2.16020546 -0.45484752

Criterion Based on Final Seeds = 3.4515

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 5 3.9382 10.0294 10 14.1206 2 9 4.0529 15.9716 9 17.3408 3 3 2.0010 5.5370 1 22.2312 4 7 3.6847 10.3631 9 15.4070 5 3 3.5561 9.5323 4 16.6547

Page 103: R Code for Calculating Beale’s F-Type Statistic: c1

6 4 4.4309 12.7349 2 18.8141 7 9 3.6262 13.1614 2 19.2516 8 5 2.4573 6.5855 4 15.8331 9 9 3.9815 13.7406 4 15.4070 10 16 3.5005 11.7523 1 14.1206

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCT1 15.50960 3.98083 0.942714 16.456278 PCT2 4.70672 2.26787 0.798116 3.953348 PCO1 9.56141 4.31734 0.822707 4.640388 PCO2 7.56983 4.72337 0.661442 1.953701 PCO3 5.43797 3.06625 0.723533 2.617070 PCO4 3.52309 3.06043 0.343826 0.523985 OVER-ALL 8.69298 3.66760 0.845215 5.460559

18:24 Saturday, November 21, 2009 187 Clustering based on Monthly Average Temperature and Ozone 10 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=10 Maxiter=1

Pseudo F Statistic = 36.40

Approximate Expected Over-All R-Squared = 0.77671

Cubic Clustering Criterion = 5.862

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -22.13967359 2.48095299 7.08561916 -2.96878269 4.71507087 -0.96823772 2 14.41750510 -0.55977218 -5.69576691 8.56520829 -5.35324848 -1.03146529 3 -27.16955932 -13.13602015 -7.52447780 -5.06162668 7.34988669 -1.47792820 4 -4.72174041 3.09696825 12.41008922 1.98124480 -0.72723325 -1.82531655 5 4.41819412 0.77393161 9.52678317 11.19681170 2.58533352 7.35250808 6 20.09811228 5.46673711 6.02340699 4.95906063 6.17520453 -2.49196720 7 23.30670087 -4.13857205 -17.73273716 0.76747707 3.04409326 0.57815439 8 -6.57631370 -6.28349794 2.81470239 4.61920000 5.91557237 2.18676526 9 1.21844578 1.42122864 0.24689498 -0.53131208 -7.42812844 -1.47577622 10 -11.62438124 2.62795653 2.63510659 -8.72343483 -0.93334433 1.02440571

Cluster Standard Deviations

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 5.378972289 0.890094499 4.913692284 4.452080685 1.005789866 4.283901995 2 4.541215420 2.310438449 4.729791174 5.545417694 3.473143630 2.721922864 3 3.327009663 2.525266688 1.438464580 1.271733954 1.636176032 0.464353724 4 1.968764046 3.044439589 4.170314685 6.297626412 3.065877283 1.366221719 5 1.719298805 0.394336093 5.161221397 2.155104953 1.704525973 6.210974087 6 8.569551835 4.260969897 3.350585095 1.614429824 2.467270300 2.506960588 7 1.642922651 1.540860056 4.207946977 5.891985392 3.460164643 3.070447413 8 3.788373577 2.309705105 2.271767694 1.983790948 1.579671930 2.225194804 9 3.338685289 2.896641670 4.606600927 5.587896248 3.167754125 3.619117657 10 3.918442181 1.463277271 4.584847355 3.757197057 3.574910062 2.847756369

18:24 Saturday, November 21, 2009 188

Page 104: R Code for Calculating Beale’s F-Type Statistic: c1

Clustering based on Monthly Average Temperature and Ozone 10 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 5003.40 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 189 Clustering based on Monthly Average Temperature and Ozone 12 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=12 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 26.17447188 -7.17847001 -22.67064748 -9.53709355 7.08928951 -3.23676902 2 -10.70761073 -8.80120169 2.46756897 7.36839188 8.35769514 -0.32727043 3 -25.24870940 -14.59398355 -6.70417273 -5.44491369 8.18469507 -1.98514609 4 15.69438709 3.21336035 9.64752659 6.92825558 5.37257111 1.04595794 5 2.50439360 0.48683436 10.95847761 12.37348243 2.11023068 12.44931239 6 7.10205831 2.54042760 1.52543058 15.88510614 -3.98916959 -4.60274869 7 31.80245481 9.14494722 6.01546199 5.37368726 3.75060905 -4.85953725 8 -3.56521911 4.64405000 14.53834421 5.31733870 2.58507837 -4.49545662 9 -17.37009706 1.26523049 4.47086690 -16.90830816 0.47613678 -0.44864696 10 15.27726935 -2.26486488 -11.44422976 2.81056112 -7.90445907 -2.17044852 11 -2.61936587 0.85526687 -2.47944102 -7.31440494 -9.72389792 4.00458550 12 -28.99302565 2.11735872 0.82753041 -1.62598581 6.13963538 -4.20728037

Criterion Based on Final Seeds = 3.2143

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 4 3.1188 7.7695 10 17.1734 2 5 2.4573 6.5855 8 15.9065 3 3 2.0010 5.5370 12 22.3710 4 3 3.3808 7.4931 6 16.5952 5 2 1.6050 2.7799 8 18.1556 6 5 3.3009 9.1883 4 16.5952 7 1 . 0 4 16.9798 8 6 3.4267 10.1461 2 15.9065 9 14 3.3776 12.7382 11 13.7872 10 12 4.2603 14.8563 1 17.1734 11 12 3.7447 13.3224 9 13.7872 12 3 3.8989 9.8108 9 15.3279

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCT1 15.50960 4.03964 0.942975 16.536219 PCT2 4.70672 2.16630 0.821934 4.615896 PCO1 9.56141 4.55043 0.809611 4.252417

Page 105: R Code for Calculating Beale’s F-Type Statistic: c1

18:24 Saturday, November 21, 2009 190 Clustering based on Monthly Average Temperature and Ozone 12 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=12 Maxiter=1

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCO2 7.56983 3.53734 0.816447 4.448015 PCO3 5.43797 3.40829 0.669799 2.028457 PCO4 3.52309 2.96819 0.403357 0.676045 OVER-ALL 8.69298 3.52745 0.861591 6.224978

Pseudo F Statistic = 32.82

Approximate Expected Over-All R-Squared = 0.80497

Cubic Clustering Criterion = 5.257

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 24.49777868 -5.47238895 -18.02539876 -4.66355725 6.35012675 -0.45634479 2 -6.57631370 -6.28349794 2.81470239 4.61920000 5.91557237 2.18676526 3 -27.16955932 -13.13602015 -7.52447780 -5.06162668 7.34988669 -1.47792820 4 16.19666477 4.24066707 6.02605532 4.82085176 6.98340302 -1.70277719 5 3.71115371 0.85519515 12.38974643 12.44046106 3.29361838 10.81149395 6 6.81204174 1.45473342 0.74540576 12.11411234 -2.93957618 -1.53839990 7 31.80245481 9.14494722 6.01546199 5.37368726 3.75060905 -4.85953725 8 -4.69766055 3.12686922 12.95214051 3.66940870 -0.42525706 -1.94305107 9 -13.70279042 2.43343231 4.36087337 -8.81609733 0.49605322 0.54009370 10 18.35158318 -2.08553457 -11.91432883 5.51887269 -3.86811983 0.03189563 11 -2.54452498 2.15597866 0.87157245 -4.83639202 -5.60578112 0.03385954 12 -25.04516757 2.72983444 7.24979109 -0.44182497 5.22513527 -1.77661652

18:24 Saturday, November 21, 2009 191 Clustering based on Monthly Average Temperature and Ozone 12 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=12 Maxiter=1

Cluster Standard Deviations

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 1.144013073 1.137418707 5.363176134 3.261352302 1.041538456 3.908011016 2 3.788373577 2.309705105 2.271767694 1.983790948 1.579671930 2.225194804 3 3.327009663 2.525266688 1.438464580 1.271733954 1.636176032 0.464353724 4 4.339132619 4.267822663 4.103606783 1.948067075 2.282986047 2.385445831 5 1.706616504 0.520940813 2.024119787 0.094722089 1.673562940 2.316225053 6 5.160759188 2.700433173 2.690856181 2.727543521 2.573483652 3.185564482 7 . . . . . . 8 2.155543456 3.333890328 4.289725504 4.863432958 3.242457619 1.457202198 9 3.512110502 1.434072335 4.301082535 3.815844432 3.749107703 2.634856657 10 4.844350652 1.853547378 5.858750860 3.871147016 5.125885237 2.532650710 11 4.498573662 2.068916401 4.624717864 3.658788132 2.858468388 4.083222535 12 5.078012278 0.760519933 6.237731004 2.987388106 0.792083603 4.047791085

Page 106: R Code for Calculating Beale’s F-Type Statistic: c1

18:24 Saturday, November 21, 2009 192 Clustering based on Monthly Average Temperature and Ozone 12 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 4339.33 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 193 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=50 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -7.86891703 2.60659500 17.61728069 9.43806143 -2.92259233 -1.80934960 2 1.54718311 4.88127310 10.20747823 -5.34320472 -9.32655058 -2.83482547 3 7.84308181 -3.00296132 -6.16920087 3.95011115 -12.42265368 -0.85869913 4 24.13549460 -2.31522955 -20.74774458 9.36293579 -1.92570126 2.55375831 5 2.50439360 0.48683436 10.95847761 12.37348243 2.11023068 12.44931239 6 18.87002003 -3.81007102 -8.70793720 6.34263287 1.28387081 -2.44534488 7 -3.96970822 -4.43483810 0.69294273 2.31650915 5.60732222 2.52557376 8 -19.31663853 2.49105331 13.28496355 -2.65559737 4.75509464 2.89610135 9 1.63252491 -1.64373523 1.02427673 -0.38896807 -8.45618803 -8.14182229 10 -13.95026216 3.92123596 2.84372256 -5.13575493 1.98571299 2.58459092 11 31.80245481 9.14494722 6.01546199 5.37368726 3.75060905 -4.85953725 12 -31.01125917 -10.22009334 -9.18543209 -6.09763360 5.46469736 -1.37489115 13 -28.99302565 2.11735872 0.82753041 -1.62598581 6.13963538 -4.20728037 14 14.07056791 -1.94979421 -12.53842840 1.94963998 -7.87801441 3.83149139 15 -14.32370049 0.25789423 11.43960634 -5.40708377 -0.65915818 0.88714238 16 24.28326217 -4.91563523 -22.66652374 -3.02164952 4.85089941 5.33374256 17 21.61690260 2.54182208 -4.73772104 15.18448813 -8.14898308 -0.28153788 18 -8.47392895 1.82027023 5.36416814 -8.59663006 -3.49199781 1.51693244 19 -26.82583853 3.58109128 7.63687931 2.95610827 4.78067579 -4.01867055 20 12.13052904 0.58025875 1.56894518 3.08589940 5.98162759 -3.23107078 21 -2.61936587 0.85526687 -2.47944102 -7.31440494 -9.72389792 4.00458550 22 -12.35931012 2.88510974 2.27700435 -14.51029140 -1.77494551 3.16558403 23 15.69438709 3.21336035 9.64752659 6.92825558 5.37257111 1.04595794 24 -17.37009706 1.26523049 4.47086690 -16.90830816 0.47613678 -0.44864696 25 22.32666260 -2.45349958 -16.40553692 3.57519633 2.98679251 4.48657294 26 8.76906458 -2.34860854 -0.09681579 13.57050486 -2.47553032 2.67415329 27 -6.15795637 2.03785071 -0.53023004 -11.65566108 -4.03533635 4.36754609 28 23.76669035 -4.89772528 -13.21754614 -3.39438963 6.43731625 -2.08912917 29 -4.30168153 4.86827149 17.62711647 0.88212599 -0.58601647 -2.65441445 30 -18.43210136 1.22793573 3.79331726 -9.36150186 4.59820937 -3.98278246 31 -5.19929675 5.54301971 7.36407668 4.93954603 1.23284668 -1.24908142 32 -5.97310220 3.70101563 -0.79353059 -4.86430426 -3.59730755 -2.00247898 33 -5.76840458 4.47692301 -0.73428048 -6.26858594 8.18331923 -1.13214014 34 1.44229595 -1.22346114 -3.67077986 0.71568701 -3.50990904 -1.63295747 35 -1.48244429 -3.37764387 9.83646851 5.98694735 2.59902230 -0.97958320 36 20.36180286 -3.47148538 -21.69368282 2.30940782 -0.24742673 0.77882556 37 20.76507818 8.92838212 6.86169418 4.44840029 9.59601036 -2.92321872 38 -0.92288883 5.03435131 1.87836862 11.48901258 -3.67852511 -4.63067019 39 -10.97946361 5.22546624 -6.11627726 -9.05656062 2.16020546 -0.45484752 40 13.27969971 1.43609222 -3.38081128 10.91642514 -5.72341968 -1.56727024 41 -10.70761073 -8.80120169 2.46756897 7.36839188 8.35769514 -0.32727043 42 0.96403506 2.92824421 1.55743749 -3.22931863 -4.45289551 -1.50728300 43 13.99418618 0.07354821 -6.20202551 2.59170848 -9.67136849 -1.50718189 44 26.17447188 -7.17847001 -22.67064748 -9.53709355 7.08928951 -3.23676902

Page 107: R Code for Calculating Beale’s F-Type Statistic: c1

18:24 Saturday, November 21, 2009 194 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=50 Maxiter=1

Initial Seeds

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 45 -3.25721263 -4.40197237 6.58956560 5.47373504 6.46936475 4.11502522 46 5.83227494 0.61140452 3.80085666 8.70951297 1.16876380 0.43453632 47 -5.76840458 4.47692301 10.72955647 -4.54756726 -5.45988088 -0.47042111 48 -25.24870940 -14.59398355 -6.70417273 -5.44491369 8.18469507 -1.98514609 49 7.10205831 2.54042760 1.52543058 15.88510614 -3.98916959 -4.60274869 50 -10.82576302 4.76445441 -5.35884936 -4.24289791 -2.13502111 7.51994881

Criterion Based on Final Seeds = 0.8654

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 1 . 0 29 9.0077 2 1 . 0 47 9.0632 3 1 . 0 43 8.5178 4 1 . 0 25 7.2216 5 2 1.6050 2.7799 46 14.2984 6 2 1.7000 2.9444 25 7.7558 7 2 0.9975 1.7276 45 6.0820 8 2 1.3973 2.4202 15 9.7616 9 1 . 0 34 9.5030 10 2 1.8184 3.1495 30 7.1000 11 1 . 0 37 12.7028 12 1 . 0 48 8.3054 13 1 . 0 19 8.7226 14 1 . 0 43 6.9568 15 3 1.7052 4.0186 18 6.3610 16 1 . 0 36 9.6732 17 1 . 0 40 9.9778 18 2 1.8168 4.1826 15 6.3610 19 1 . 0 13 8.7226 20 1 . 0 46 10.6243 21 2 1.9292 3.3415 42 8.5452 22 1 . 0 18 6.6506 23 1 . 0 37 10.2896 24 1 . 0 22 7.5117 25 2 1.6534 2.8637 36 7.1317 26 1 . 0 46 8.6316 27 1 . 0 32 7.4806

18:24 Saturday, November 21, 2009 195 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=50 Maxiter=1

Cluster Summary

Maximum Distance RMS Std from Seed Radius Nearest Distance Between Cluster Frequency Deviation to Observation Exceeded Cluster Cluster Centroids

Page 108: R Code for Calculating Beale’s F-Type Statistic: c1

ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 28 2 0.2883 0.4994 6 10.5770 29 2 1.8985 3.2882 1 9.0077 30 2 1.2271 2.1254 10 7.1000 31 1 . 0 29 9.3320 32 2 1.5423 5.3429 27 7.4806 33 1 . 0 39 10.0594 34 1 . 0 42 7.3057 35 1 . 0 45 7.4793 36 1 . 0 25 7.1317 37 1 . 0 23 10.2896 38 1 . 0 49 9.4956 39 1 . 0 33 10.0594 40 2 1.8525 3.2086 43 9.0321 41 2 1.6511 2.8597 7 8.9801 42 2 1.2590 2.1807 34 7.3057 43 2 1.7843 3.0905 14 6.9568 44 1 . 0 16 11.3847 45 1 . 0 7 6.0820 46 1 . 0 26 8.6316 47 2 1.5174 2.6282 18 8.8599 48 2 0.5864 1.0157 12 8.3054 49 1 . 0 26 9.4824 50 1 . 0 39 10.2970

Statistics for Variables

Variable Total STD Within STD R-Square RSQ/(1-RSQ) ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ PCT1 15.50960 1.30491 0.997948 486.368872 PCT2 4.70672 0.83436 0.990891 108.786028 PCO1 9.56141 1.83083 0.989372 93.094654 PCO2 7.56983 2.10645 0.977555 43.554275 PCO3 5.43797 1.46426 0.978984 46.583321 PCO4 3.52309 1.48286 0.948651 18.474584 OVER-ALL 8.69298 1.55622 0.990711 106.649818

Pseudo F Statistic = 43.53

18:24 Saturday, November 21, 2009 196 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=50 Maxiter=1

Approximate Expected Over-All R-Squared = .

Cubic Clustering Criterion = .

WARNING: The two values above are invalid for correlated variables.

Cluster Means

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 -7.86891703 2.60659500 17.61728069 9.43806143 -2.92259233 -1.80934960 2 1.54718311 4.88127310 10.20747823 -5.34320472 -9.32655058 -2.83482547 3 7.84308181 -3.00296132 -6.16920087 3.95011115 -12.42265368 -0.85869913 4 24.13549460 -2.31522955 -20.74774458 9.36293579 -1.92570126 2.55375831 5 3.71115371 0.85519515 12.38974643 12.44046106 3.29361838 10.81149395 6 20.48376703 -3.98333310 -10.70709077 4.94733753 1.33126728 -2.14560942 7 -4.10456722 -4.70655697 1.08840214 3.54643455 5.11193136 3.51461764 8 -18.22370121 2.73918962 11.58518441 -3.40626704 4.02841691 3.68377239 9 1.63252491 -1.64373523 1.02427673 -0.38896807 -8.45618803 -8.14182229

Page 109: R Code for Calculating Beale’s F-Type Statistic: c1

10 -14.05965632 3.27191235 3.09232667 -4.33961857 1.91643878 -0.37944249 11 31.80245481 9.14494722 6.01546199 5.37368726 3.75060905 -4.85953725 12 -31.01125917 -10.22009334 -9.18543209 -6.09763360 5.46469736 -1.37489115 13 -28.99302565 2.11735872 0.82753041 -1.62598581 6.13963538 -4.20728037 14 14.07056791 -1.94979421 -12.53842840 1.94963998 -7.87801441 3.83149139 15 -14.57113611 0.82933095 8.42196430 -8.49609497 -1.96844140 1.14873831 16 24.28326217 -4.91563523 -22.66652374 -3.02164952 4.85089941 5.33374256 17 21.61690260 2.54182208 -4.73772104 15.18448813 -8.14898308 -0.28153788 18 -10.59205652 2.05018384 5.29561241 -9.89307778 -4.91316658 2.80438650 19 -26.82583853 3.58109128 7.63687931 2.95610827 4.78067579 -4.01867055 20 12.13052904 0.58025875 1.56894518 3.08589940 5.98162759 -3.23107078 21 -2.79554950 1.26534339 -0.84846574 -4.51968883 -9.62104850 3.30796687 22 -12.35931012 2.88510974 2.27700435 -14.51029140 -1.77494551 3.16558403 23 15.69438709 3.21336035 9.64752659 6.92825558 5.37257111 1.04595794 24 -17.37009706 1.26523049 4.47086690 -16.90830816 0.47613678 -0.44864696 25 22.58719078 -2.70714127 -16.17268384 5.16856842 1.39539831 2.77102939 26 8.76906458 -2.34860854 -0.09681579 13.57050486 -2.47553032 2.67415329 27 -6.15795637 2.03785071 -0.53023004 -11.65566108 -4.03533635 4.36754609 28 23.76669035 -4.89772528 -13.38221190 -3.04774296 6.73015904 -1.96117634 29 -3.93345032 4.75616074 16.08273034 3.09973234 0.99953095 -3.57493553 30 -17.60709632 2.04790584 4.61386868 -9.28550112 3.24853484 -3.16809198 31 -5.19929675 5.54301971 7.36407668 4.93954603 1.23284668 -1.24908142 32 -6.36508991 2.69610433 0.33864010 -6.88473706 -3.90397417 -1.28482716 33 -5.76840458 4.47692301 -0.73428048 -6.26858594 8.18331923 -1.13214014 34 1.44229595 -1.22346114 -3.67077986 0.71568701 -3.50990904 -1.63295747 35 -1.48244429 -3.37764387 9.83646851 5.98694735 2.59902230 -0.97958320 36 20.36180286 -3.47148538 -21.69368282 2.30940782 -0.24742673 0.77882556

18:24 Saturday, November 21, 2009 197 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=50 Maxiter=1

Cluster Means

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 37 20.76507818 8.92838212 6.86169418 4.44840029 9.59601036 -2.92321872 38 -0.92288883 5.03435131 1.87836862 11.48901258 -3.67852511 -4.63067019 39 -10.97946361 5.22546624 -6.11627726 -9.05656062 2.16020546 -0.45484752 40 15.02873846 0.08979559 -4.53008753 9.37611650 -4.69779106 -2.39078521 41 -10.70761073 -8.80120169 2.65357102 5.26469794 6.44231718 -0.10521711 42 2.50745705 3.10745214 0.32442172 -3.08253450 -5.10861627 -0.89947259 43 14.63572776 -1.09565833 -8.82312764 2.70113480 -8.78791378 -1.83881520 44 26.17447188 -7.17847001 -22.67064748 -9.53709355 7.08928951 -3.23676902 45 -3.25721263 -4.40197237 6.58956560 5.47373504 6.46936475 4.11502522 46 5.83227494 0.61140452 3.80085666 8.70951297 1.16876380 0.43453632 47 -5.31731208 3.69724271 9.94366900 -6.34765295 -3.99948563 -0.79466529 48 -25.24870940 -14.59398355 -6.69400065 -4.54362322 8.29248136 -1.52944673 49 7.10205831 2.54042760 1.52543058 15.88510614 -3.98916959 -4.60274869 50 -10.82576302 4.76445441 -5.35884936 -4.24289791 -2.13502111 7.51994881

Cluster Standard Deviations

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 1 . . . . . . 2 . . . . . . 3 . . . . . . 4 . . . . . . 5 1.706616504 0.520940813 2.024119787 0.094722089 1.673562940 2.316225053 6 2.282182900 0.245029575 2.827230094 1.973245591 0.067028723 0.423889953 7 0.190719426 0.384268508 0.559264064 1.739377183 0.700588469 1.398719272 8 1.545646789 0.350917727 2.403850722 1.061607227 1.027677504 1.113935066 9 . . . . . . 10 0.154706709 0.918282261 0.351579294 1.125906839 0.097968523 4.191776242

Page 110: R Code for Calculating Beale’s F-Type Statistic: c1

11 . . . . . . 12 . . . . . . 13 . . . . . . 14 . . . . . . 15 0.362247568 0.662685889 2.629999883 2.769422546 1.451248301 0.429093875 16 . . . . . . 17 . . . . . . 18 2.995484736 0.325146939 0.096952448 1.833453949 2.009836145 1.820734997 19 . . . . . . 20 . . . . . . 21 0.249161278 0.579935785 2.306547353 3.952325421 0.145451047 0.985167513 22 . . . . . . 23 . . . . . . 24 . . . . . .

18:24 Saturday, November 21, 2009 198 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method

The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=50 Maxiter=1

Cluster Standard Deviations

Cluster PCT1 PCT2 PCO1 PCO2 PCO3 PCO4 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 25 0.368442484 0.358703518 0.329303978 2.253368426 2.250571271 2.426144949 26 . . . . . . 27 . . . . . . 28 0.000000000 0.000000000 0.232872554 0.490232422 0.414142235 0.180952617 29 0.520757566 0.158548536 2.184091806 3.136168989 2.242302664 1.301813407 30 1.166733304 1.159612849 1.160434949 0.107481279 1.908728022 1.152146320 31 . . . . . . 32 0.554354344 1.421159187 1.601131149 2.857323468 0.433692093 1.014912930 33 . . . . . . 34 . . . . . . 35 . . . . . . 36 . . . . . . 37 . . . . . . 38 . . . . . . 39 . . . . . . 40 2.473514313 1.903950956 1.625322057 2.178325376 1.450457903 1.164626034 41 0.000000000 0.000000000 0.263046631 2.975072499 2.708753492 0.314030821 42 2.182728316 0.253438278 1.743747619 0.207584113 0.927329198 0.859573726 43 0.907276814 1.653507748 3.706798176 0.154752186 1.249393635 0.469000338 44 . . . . . . 45 . . . . . . 46 . . . . . . 47 0.637941133 1.102634454 1.111412727 2.545705600 2.065310762 0.458550510 48 0.000000000 0.000000000 0.014385486 1.274617197 0.152432838 0.644456214 49 . . . . . . 50 . . . . . .

18:24 Saturday, November 21, 2009 199 Clustering based on Monthly Average Temperature and Ozone 7 Clusters, NH method Beale's Intracluster Residual SS

The MEANS Procedure

Analysis Variable : DISTANCE Distance to Cluster Seed

USS ƒƒƒƒƒƒƒƒƒƒƒƒ 314.5639380 ƒƒƒƒƒƒƒƒƒƒƒƒ

18:24 Saturday, November 21, 2009 200 Canonical Correlation using Monthly Means

Page 111: R Code for Calculating Beale’s F-Type Statistic: c1

The CANCORR Procedure

VAR Variables 6 WITH Variables 6 Observations 70

Means and Standard Deviations

Standard Variable Mean Deviation

TempApril 58.948187 8.634204 TempMay 66.594223 6.636108 TempJune 74.115753 6.055944 TempJuly 79.251062 5.360098 TempAug 77.188558 6.954290 TempSep 70.985671 6.417539 O3April 2.867204 4.870968 O3May 6.606144 3.802739 O3June 4.862348 5.979171 O3July 4.839117 7.597984 O3Aug 4.860275 6.535204 O3Sep 1.093177 5.260907

18:24 Saturday, November 21, 2009 201 Canonical Correlation using Monthly Means

The CANCORR Procedure

Correlations Among the Original Variables

Correlations Among the VAR Variables

TempApril TempMay TempJune TempJuly TempAug TempSep

TempApril 1.0000 0.9203 0.7930 0.5688 0.8359 0.8797 TempMay 0.9203 1.0000 0.9455 0.7922 0.9151 0.9366 TempJune 0.7930 0.9455 1.0000 0.9097 0.9223 0.8799 TempJuly 0.5688 0.7922 0.9097 1.0000 0.8411 0.6887 TempAug 0.8359 0.9151 0.9223 0.8411 1.0000 0.8829 TempSep 0.8797 0.9366 0.8799 0.6887 0.8829 1.0000

Correlations Among the WITH Variables

O3April O3May O3June O3July O3Aug O3Sep

O3April 1.0000 0.6151 -0.1324 -0.2089 0.0429 0.3763 O3May 0.6151 1.0000 0.3516 0.1985 0.3100 0.3513 O3June -0.1324 0.3516 1.0000 0.8276 0.1207 -0.1941 O3July -0.2089 0.1985 0.8276 1.0000 0.1574 -0.2757 O3Aug 0.0429 0.3100 0.1207 0.1574 1.0000 0.4358 O3Sep 0.3763 0.3513 -0.1941 -0.2757 0.4358 1.0000

Correlations Between the VAR Variables and the WITH Variables

O3April O3May O3June O3July O3Aug O3Sep

TempApril 0.2729 0.0938 -0.5998 -0.7258 0.2701 0.5091 TempMay 0.1972 0.1318 -0.4098 -0.5634 0.2784 0.4440 TempJune 0.0697 0.0308 -0.2891 -0.4266 0.3322 0.3435 TempJuly -0.0997 -0.0038 -0.1424 -0.1925 0.3991 0.2114 TempAug 0.2372 0.1759 -0.3879 -0.4732 0.5371 0.4883 TempSep 0.3391 0.2501 -0.2911 -0.4673 0.3154 0.5475

18:24 Saturday, November 21, 2009 202 Canonical Correlation using Monthly Means

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The CANCORR Procedure

Canonical Correlation Analysis

Adjusted Approximate Squared Canonical Canonical Standard Canonical Correlation Correlation Error Correlation

1 0.969548 0.965315 0.007220 0.940022 2 0.751795 0.690103 0.052344 0.565195 3 0.705846 . 0.060407 0.498219 4 0.504496 0.468872 0.089746 0.254516 5 0.311509 0.236436 0.108704 0.097038 6 0.246526 . 0.113069 0.060775

Test of H0: The canonical correlations in the current row and all Eigenvalues of Inv(E)*H that follow are zero = CanRsq/(1-CanRsq) Likelihood Approximate Eigenvalue Difference Proportion Cumulative Ratio F Value Num DF Den DF Pr > F

1 15.6729 14.3730 0.8481 0.8481 0.00827323 14.16 36 257.46 <.0001 2 1.2999 0.3070 0.0703 0.9185 0.13793878 6.22 25 220.68 <.0001 3 0.9929 0.6515 0.0537 0.9722 0.31724302 5.24 16 183.94 <.0001 4 0.3414 0.2339 0.0185 0.9907 0.63223377 3.42 9 148.61 0.0007 5 0.1075 0.0428 0.0058 0.9965 0.84808473 2.66 4 124 0.0357 6 0.0647 0.0035 1.0000 0.93922502 4.08 1 63 0.0477

Multivariate Statistics and F Approximations

S=6 M=-0.5 N=28

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.00827323 14.16 36 257.46 <.0001 Pillai's Trace 2.41576504 7.08 36 378 <.0001 Hotelling-Lawley Trace 18.47927951 29.12 36 156.69 <.0001 Roy's Greatest Root 15.67291262 164.57 6 63 <.0001

NOTE: F Statistic for Roy's Greatest Root is an upper bound.

18:24 Saturday, November 21, 2009 203 Canonical Correlation using Monthly Means

The CANCORR Procedure

Canonical Correlation Analysis

Raw Canonical Coefficients for the VAR Variables

Temp1 Temp2

TempApril 0.1059787775 -0.242586636 TempMay -0.069267267 0.2414996903 TempJune -0.047745711 -0.36759019 TempJuly -0.07862957 -0.092037538 TempAug 0.2468015051 0.1630793622 TempSep -0.11650095 0.3038222457

Raw Canonical Coefficients for the WITH Variables

Oz1 Oz2

O3April 0.0226380356 0.1081019138 O3May 0.0343880965 0.0718560625 O3June -0.074174983 0.044034583

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O3July -0.058405117 0.0341561902 O3Aug 0.1018595881 -0.021140302 O3Sep -0.012926164 0.0793110957

18:24 Saturday, November 21, 2009 204 Canonical Correlation using Monthly Means

The CANCORR Procedure

Canonical Correlation Analysis

Standardized Canonical Coefficients for the VAR Variables

Temp1 Temp2

TempApril 0.9150 -2.0945 TempMay -0.4597 1.6026 TempJune -0.2891 -2.2261 TempJuly -0.4215 -0.4933 TempAug 1.7163 1.1341 TempSep -0.7476 1.9498

Standardized Canonical Coefficients for the WITH Variables

Oz1 Oz2

O3April 0.1103 0.5266 O3May 0.1308 0.2732 O3June -0.4435 0.2633 O3July -0.4438 0.2595 O3Aug 0.6657 -0.1382 O3Sep -0.0680 0.4172

18:24 Saturday, November 21, 2009 205 Canonical Correlation using Monthly Means

The CANCORR Procedure

Canonical Structure

Correlations Between the VAR Variables and Their Canonical Variables

Temp1 Temp2

TempApril 0.8000 -0.0025 TempMay 0.6455 0.0433 TempJune 0.5436 -0.0589 TempJuly 0.4006 -0.1436 TempAug 0.7793 0.1032 TempSep 0.5975 0.3110

Correlations Between the WITH Variables and Their Canonical Variables

Oz1 Oz2

O3April 0.3450 0.7567 O3May 0.1371 0.8450 O3June -0.6859 0.4068 O3July -0.6843 0.2849 O3Aug 0.5579 0.2236 O3Sep 0.5180 0.5285

Correlations Between the VAR Variables and the Canonical Variables of the WITH Variables

Oz1 Oz2

TempApril 0.7756 -0.0019 TempMay 0.6259 0.0325 TempJune 0.5270 -0.0443

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TempJuly 0.3884 -0.1079 TempAug 0.7555 0.0776 TempSep 0.5793 0.2338

Correlations Between the WITH Variables and the Canonical Variables of the VAR Variables

Temp1 Temp2

O3April 0.3345 0.5689 O3May 0.1329 0.6353 O3June -0.6650 0.3058 O3July -0.6635 0.2142 O3Aug 0.5409 0.1681 O3Sep 0.5022 0.3974

18:24 Saturday, November 21, 2009 206 Canonical Correlation using Monthly Means

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

1 Akron 0 64.2845 336.711 32.4186 97.2557 51.4000 61.6129 70.0667 2 Arlington 1 15.8351 160.462 16.8907 32.7258 56.7667 67.4839 74.9333 3 Atlanta 1 21.5268 206.496 21.3919 42.9862 65.3667 69.1290 75.1667 4 Austin 1 34.7171 161.644 12.1879 47.3974 72.0000 76.6452 81.9667 5 Bakersfield 1 47.6086 289.430 19.0434 66.9543 58.0667 66.6452 73.9000 6 Baton Rouge 1 22.2840 370.108 19.8618 42.1459 72.0333 74.7419 80.5000 7 Boston 1 29.5735 242.242 29.4285 59.1470 49.4000 58.4194 71.2000 8 Buffalo 1 42.5145 427.039 31.8858 74.8212 46.1333 59.8387 68.5667 9 Charlotte 1 31.7778 216.549 28.7582 60.8236 62.2333 65.9677 73.6333

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

1 76.0968 68.4516 63.7333 -2.59742 2.9776 9.3160 10.1753 -1.3167 -5.4473 2 83.2258 79.9032 70.2667 -5.77401 3.3453 6.7535 13.4359 8.1736 -6.5235 3 79.3871 82.1290 73.3000 -4.00079 2.8535 -1.9897 -0.0305 13.6344 2.2994 4 83.4516 88.5161 81.6667 8.26811 2.1398 -5.5971 -11.3581 9.2746 11.6430 5 80.2258 77.8710 77.2333 2.01369 10.1284 14.0376 13.9645 9.5357 16.2752 6 81.8710 85.2903 76.3000 4.48913 13.4318 0.1609 -3.6472 8.2088 3.4473 7 76.0323 71.6452 67.3667 6.72094 2.6733 7.3469 7.7088 3.5155 -3.5027 8 74.5806 68.0645 64.4667 2.51458 9.0380 13.3186 15.9207 1.0480 0.3954 9 79.0645 79.6774 69.3667 0.53066 2.7441 4.2031 3.6292 12.7265 -6.9343

Obs PCT1 PCT2 PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3

1 -14.9869 0.6743 -0.74777 3.34990 -0.46525 -0.06240 7.2086 -10.7570 -1.7173 2 1.5472 4.8813 -1.07394 -0.88940 0.67658 -1.13189 10.2075 -5.3432 -9.3266 3 7.8431 -3.0030 -1.72760 -2.23032 -0.07069 -0.11761 -6.1692 3.9501 -12.4227 4 24.1355 -2.3152 1.03536 -1.88439 -0.61332 -0.41074 -20.7477 9.3629 -1.9257 5 2.5044 0.4868 5.21203 -1.45462 2.30347 0.42333 10.9585 12.3735 2.1102 6 18.8700 -3.8101 -2.61150 0.00562 -1.30199 0.00649 -8.7079 6.3426 1.2839 7 -14.1691 2.6226 2.33049 -0.90634 -0.53725 2.55027 3.3409 -3.5435 1.8472 8 -19.3166 2.4911 2.34841 1.39937 -0.90051 -0.76557 13.2850 -2.6556 4.7551 9 1.6325 -1.6437 -3.36313 -1.80680 -0.02224 0.57017 1.0243 -0.3890 -8.4562

Obs PCO4 PCO5 PCO6 Temp1 Temp2 Oz1 Oz2

1 0.9151 -0.65715 0.61300 -1.32495 -1.22142 -1.43513 -0.86124 2 -2.8348 1.24694 -1.56791 0.10936 0.30195 -0.51418 -1.46566 3 -0.8587 0.44206 -1.19877 1.39347 0.16513 1.38627 -1.56997 4 2.5538 1.23829 4.66429 1.53319 1.08099 2.00378 -0.00750 5 12.4493 0.56094 -0.04786 -0.72273 2.22521 -0.83176 1.98181 6 -2.4453 -3.69869 -4.76767 1.69196 -0.85869 1.42646 0.28483 7 -3.3435 1.75667 5.12471 -0.99985 -0.29346 -0.47747 0.00535 8 2.8961 0.56255 -0.71447 -1.75035 0.47834 -1.57811 0.91275 9 -8.1418 -1.55721 2.67765 1.23212 -0.83973 0.83888 -1.40342

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18:24 Saturday, November 21, 2009 207 Canonical Correlation using Monthly Means

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

10 Chicago 0 33.0126 328.191 31.1527 64.5372 49.8000 61.8710 70.5667 11 Cincinnati 0 53.2828 352.704 32.5355 85.8184 55.3000 63.7742 73.2667 12 Cleveland 0 38.3076 427.984 24.1754 62.9135 50.5667 61.2581 70.4000 13 Colorado Springs 0 43.7197 170.430 17.0236 62.0975 42.5333 53.4839 63.0333 14 ColumbusGA 1 47.7747 654.889 30.5973 78.3720 68.2667 71.8548 78.3667 15 ColumbusOH 0 39.9447 273.252 19.6449 59.8703 55.1667 65.0323 74.7333 16 Corpus Christi 1 39.8540 256.660 23.5936 63.4475 74.9000 78.8387 82.9667 17 Dallas/Fort Worth 1 30.9771 216.197 15.8576 46.9062 68.2833 73.8871 82.1167 18 Dayton 0 48.6529 348.441 31.3024 81.7441 53.8333 63.8065 72.7333

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

10 78.5806 70.5484 63.6667 1.25153 6.0385 7.6226 7.0373 -0.5158 0.0429 11 79.1935 72.9677 67.0667 -3.08945 3.1260 4.7007 5.7707 0.9676 -4.9646 12 76.4194 69.3548 65.1667 -4.30625 3.4514 9.1086 9.1632 0.2957 -4.3639 13 71.3226 69.0323 57.9000 8.53664 8.9151 5.4381 5.8312 2.1564 -2.5394 14 82.0323 84.3387 75.0833 -2.64460 2.9716 -2.1978 -5.9310 7.2687 6.1511 15 80.3548 73.3226 68.1000 -3.24023 5.2574 14.5176 7.3581 2.5967 -7.1603 16 82.9355 84.3871 79.8000 5.98796 4.8851 -5.2161 -13.0445 -5.0587 7.7383 17 86.0484 90.2097 79.2667 3.47606 5.2499 1.2840 0.5819 19.9481 9.1287 18 78.6452 71.5806 67.0000 -3.47475 2.9661 8.3600 8.3384 0.7234 -3.7851

Obs PCT1 PCT2 PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3

10 -13.9503 3.9212 -1.10673 2.26395 0.01041 -0.60606 2.8437 -5.1358 1.98571 11 -6.7571 1.6912 -0.99259 2.20802 -0.02399 0.88352 1.4708 -8.9052 -4.21064 12 -14.4028 1.5558 0.53504 2.33898 -0.31330 0.24892 6.6177 -9.3242 -3.52887 13 -28.9930 2.1174 -1.88199 -3.78581 -1.16758 -0.67332 0.8275 -1.6260 6.13964 14 14.0706 -1.9498 -2.17827 -1.26909 -0.23253 0.19199 -12.5384 1.9496 -7.87801 15 -4.8662 2.9176 -0.22757 2.96128 -0.22718 0.73986 9.1578 -8.1477 -2.53909 16 24.2833 -4.9156 -0.51262 3.16668 -1.16086 -0.57813 -22.6665 -3.0216 4.85090 17 21.6169 2.5418 -0.52100 -3.78982 -0.30191 0.44379 -4.7377 15.1845 -8.14898 18 -8.4739 1.8203 -0.01526 2.88076 -0.08407 0.34482 5.3642 -8.5966 -3.49200

Obs PCO4 PCO5 PCO6 Temp1 Temp2 Oz1 Oz2

10 2.58459 -0.53973 -0.10706 -1.20631 -0.86168 -0.92325 0.01153 11 -0.56718 -0.60910 -0.67099 -0.73137 -1.35763 -0.61515 -1.26746 12 1.64395 -1.67449 -0.24452 -1.37403 -0.67440 -1.23280 -1.00379 13 -4.20728 0.59353 0.46815 -0.16745 0.31354 -0.12137 0.60709 14 3.83149 -1.66113 -0.54652 1.48881 -0.39767 1.08290 -1.18552 15 -1.11891 -7.17741 1.57135 -1.02679 -1.29567 -1.17183 -0.85268 16 5.33374 -1.29846 0.27451 0.87985 -0.65335 0.70728 -0.10422 17 -0.28154 0.71969 2.30924 1.81658 0.56940 1.91418 -0.01627 18 1.51693 -1.24442 0.37378 -1.15503 -0.99399 -1.09088 -0.97304

18:24 Saturday, November 21, 2009 208 Canonical Correlation using Monthly Means

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

19 Denver 0 40.8828 205.978 22.1123 63.208 42.5917 54.3306 63.4167 20 El Paso 1 29.8695 199.081 17.8040 47.968 63.4333 74.3548 80.2333 21 Evansville 0 58.7476 588.639 31.4096 91.320 58.0000 65.6452 74.7667 22 Fort Wayne 0 45.8040 288.686 23.2033 69.610 51.5000 62.5806 71.6333 23 Fresno 1 35.6514 265.822 8.1310 44.158 58.7333 68.2258 76.2000 24 Grand Rapids 0 35.8676 286.941 33.6041 70.690 49.0667 61.2258 69.5667 25 Houston 1 21.0847 201.672 12.5567 33.877 73.1667 76.7742 82.1667

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26 Huntsville 1 29.9964 267.076 20.5999 50.596 65.7667 69.4194 76.4667 27 Indianapolis 0 53.8088 322.272 26.2652 80.423 55.2667 64.5484 74.0000

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

19 73.1720 70.6452 58.9889 6.96790 12.1597 8.0521 11.4697 6.8247 -1.1549 20 81.3226 81.4839 75.6667 9.70463 9.3137 7.6609 5.2615 5.6874 0.4456 21 79.6452 74.6129 68.5000 -8.25527 1.0679 2.0634 2.7001 2.6426 -0.4325 22 78.6129 69.7419 64.5667 -4.89325 2.5078 6.7268 6.3050 -5.7237 -5.0256 23 80.7097 78.6452 77.4333 4.01151 12.9835 14.8018 16.4152 9.8696 13.5157 24 74.9032 68.0000 62.9667 -3.30959 3.9831 8.5222 7.1289 -6.8933 -9.5720 25 83.3226 87.0968 78.1667 6.53232 6.4918 -4.4637 -7.1414 7.2114 8.3122 26 80.7419 80.8387 74.0333 3.96797 9.1020 6.4593 3.3874 15.2416 10.0658 27 79.5161 72.6129 67.2667 -6.14490 2.6241 4.6211 4.1704 -3.3937 -2.3107

Obs PCT1 PCT2 PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3

19 -26.8258 3.5811 -1.70440 -4.40190 -0.36995 -1.10747 7.6369 2.9561 4.78068 20 12.1305 0.5803 1.50494 1.77481 -2.54866 -1.73902 1.5689 3.0859 5.98163 21 -2.6194 0.8553 -1.19690 2.29236 -0.39411 0.86946 -2.4794 -7.3144 -9.72390 22 -12.3593 2.8851 -0.78728 3.62074 -0.00792 0.06092 2.2770 -14.5103 -1.77495 23 4.9179 1.2236 5.08306 -0.56716 0.91284 0.44559 13.8210 12.5074 4.47701 24 -17.3701 1.2652 -0.06601 2.97193 -1.44123 -0.74919 4.4709 -16.9083 0.47614 25 22.8477 -2.9608 -2.02331 0.03371 -1.38042 -0.38197 -15.9398 6.7619 -0.19600 26 8.7691 -2.3486 -1.19596 -0.41012 0.47917 0.77058 -0.0968 13.5705 -2.47553 27 -6.1580 2.0379 -0.70043 3.06848 -0.30145 0.72111 -0.5302 -11.6557 -4.03534

Obs PCO4 PCO5 PCO6 Temp1 Temp2 Oz1 Oz2

19 -4.01867 0.83830 -1.98533 -0.11244 0.78662 -0.11090 0.98946 20 -3.23107 -0.72043 2.11465 -0.00245 0.46940 0.10826 1.00251 21 4.00459 -0.86949 -1.74390 -0.44291 -1.44996 -0.31588 -1.87074 22 3.16558 -1.47916 -1.00664 -1.43265 -1.35583 -1.53951 -1.26278 23 9.17368 0.71421 -1.42310 -0.74166 1.74224 -0.81847 2.29438 24 -0.44865 -2.86869 -1.01336 -1.44984 -0.76180 -1.69460 -1.21422 25 1.05549 0.79779 0.07555 1.70595 -0.52735 1.61670 0.09095 26 2.67415 -1.55364 0.71884 0.84326 -0.45198 1.01853 0.81123 27 4.36755 -1.48804 -1.89348 -0.95978 -1.45894 -1.08075 -1.38930

18:24 Saturday, November 21, 2009 209 Canonical Correlation using Monthly Means

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

28 Jackson 1 31.8979 438.596 30.3030 62.201 69.5000 71.7742 79.7000 29 Jersey City 1 28.0800 278.665 16.9137 44.994 53.5667 63.5484 74.3667 30 Johnstown 0 55.0466 706.431 30.7999 86.502 47.8000 60.3226 69.7667 31 Kansas CityKS 0 41.8034 261.588 25.3354 67.139 53.6667 64.3387 72.6167 32 Kansas CityMO 0 50.7304 310.738 29.3645 80.424 54.8000 63.6452 71.7667 33 Kingston 1 46.6951 738.682 18.5655 66.948 53.0889 62.6237 73.0778 34 Knoxville 0 53.1369 305.210 29.5787 83.239 61.4000 66.3871 75.1333 35 Lafayette 1 27.2962 262.988 23.0967 50.393 73.4000 76.9032 81.5667 36 Lake Charles 1 34.8628 326.838 31.0496 65.912 72.2333 75.1290 80.7000

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

28 82.1935 84.2258 75.3667 0.10213 3.5189 -2.0668 -5.8030 10.5212 1.56816 29 81.0968 76.5484 69.5333 4.06688 5.1239 11.9726 21.1476 9.2866 -2.58669 30 76.0000 69.0968 64.9333 0.84099 7.3021 5.8602 10.3271 -1.5896 -6.29763 31 82.0000 77.8871 65.8167 4.28449 10.5564 7.0183 11.9288 8.9702 1.99419 32 81.1613 76.5484 65.9667 -1.13202 5.7234 0.9810 5.5242 3.4300 -3.16688 33 80.8710 75.8495 69.5667 8.25349 6.4617 7.5877 3.5178 -3.3418 -2.37853 34 78.8387 78.0000 70.1000 1.39910 5.3193 3.9502 -0.0561 7.6415 -0.05212 35 82.5161 85.7419 78.4333 6.51440 8.3299 -2.7520 -5.1370 5.5211 3.68539

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36 82.5484 86.0968 77.8667 6.32986 3.9044 -6.4831 -12.5135 3.5228 6.41760

Obs PCT1 PCT2 PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3

28 15.2773 -2.2649 -2.39000 -0.62519 -0.59535 1.32246 -11.4442 2.8106 -7.90446 29 -4.3017 4.8683 0.64120 -0.60070 0.23792 1.09247 17.6271 0.8821 -0.58602 30 -16.7821 2.8679 1.58015 1.58502 -0.57091 -0.09434 5.4344 -9.2095 1.89886 31 -5.1993 5.5430 -3.10141 -1.18550 0.40062 -1.02463 7.3641 4.9395 1.23285 32 -5.9731 3.7010 -3.07946 -0.70748 1.06065 -0.43332 -0.7935 -4.8643 -3.59731 33 -5.7684 4.4769 0.92631 -0.92266 1.12864 1.14216 -0.7343 -6.2686 8.18332 34 1.4423 -1.2235 -1.82076 -0.05541 -0.79801 1.08190 -3.6708 0.7157 -3.50991 35 22.0975 -4.1566 -1.44665 0.79854 -1.15359 -0.54452 -12.7062 3.5520 1.37866 36 20.3618 -3.4715 -1.68571 -0.50229 -0.72039 -0.00694 -21.6937 2.3094 -0.24743

Obs PCO4 PCO5 PCO6 Temp1 Temp2 Oz1 Oz2

28 -2.17045 -2.07024 0.60662 1.48789 -1.15363 1.53724 -1.27136 29 -2.65441 5.28560 2.54378 -0.50525 -0.23784 -1.00528 0.50788 30 -2.35340 1.10024 -2.68804 -1.57573 -0.07074 -0.97792 -0.38746 31 -1.24908 1.96741 -2.15609 0.22653 -0.42198 0.00092 0.75873 32 -2.00248 1.49907 -3.00209 0.15334 -0.64750 0.03637 -0.95090 33 -1.13214 -1.13959 2.85516 -0.58892 0.04545 -0.79860 0.54482 34 -1.63296 -2.75997 1.03117 0.56147 -1.11766 0.57418 -0.60817 35 -1.84587 -0.34592 -1.19942 1.44836 -0.39794 1.32311 0.03371 36 0.77883 -0.50460 1.54554 1.64004 -0.34208 1.63545 -0.46155

18:24 Saturday, November 21, 2009 210 Canonical Correlation using Monthly Means

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

37 Las Vegas 0 45.9381 254.913 19.9162 65.854 61.2000 75.5806 85.4667 38 Lexington 0 41.8407 272.924 25.3347 67.175 56.7000 65.5161 73.6667 39 Lincoln 0 39.1544 361.180 14.3833 53.538 51.0667 61.8710 70.4000 40 Little Rock 0 74.4175 308.736 19.6418 94.059 65.6833 71.1129 78.9000 41 Los Angeles 1 30.3803 265.544 14.2027 44.804 58.8167 63.3871 65.6667 42 Louisville 0 64.0135 380.188 35.3227 99.480 59.5000 67.8065 76.5000 43 Memphis 0 32.8701 356.000 26.1847 59.278 67.2667 71.4194 79.9000 44 Miami 1 35.9019 340.691 26.0500 62.085 78.0000 78.8387 81.0667 45 Modesto 1 44.9667 293.738 14.7652 60.179 58.5167 64.8226 71.7333

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

37 88.4194 88.1935 81.9333 8.86449 15.7920 15.3006 5.3280 5.5927 -0.30987 38 79.8065 75.9355 68.9333 -6.40648 3.4592 3.4754 5.2706 7.5647 1.01188 39 80.8387 74.1935 64.1333 3.05017 3.8878 0.5766 1.2496 -3.6920 -2.70199 40 84.4677 84.2097 75.1667 2.31853 8.3827 2.2919 0.9441 16.0051 5.43948 41 71.5161 70.0968 68.6000 5.58612 10.9744 9.0467 5.5017 5.2416 2.43886 42 83.4839 78.7742 72.2667 -1.95398 3.5216 3.0344 3.9898 5.7273 -1.20572 43 83.9355 82.9032 75.4333 -2.24268 3.4254 0.2333 -1.4341 11.6956 1.00112 44 84.1613 83.8065 82.1000 7.48433 7.7844 -8.5097 -12.2927 -8.1683 -2.35173 45 74.3387 74.9032 73.4167 7.20520 10.4089 8.5813 12.2299 4.5215 7.47960

Obs PCT1 PCT2 PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3

37 20.7651 8.9284 5.02954 -1.17045 -1.40892 -0.36416 6.8617 4.4484 9.59601 38 -2.9717 1.6754 -0.69926 0.61528 0.03219 -0.04752 0.7825 -1.7250 -9.51820 39 -10.9795 5.2255 -2.61839 -0.17325 1.22765 -0.65754 -6.1163 -9.0566 2.16021 40 13.2797 1.4361 -1.54032 -1.07223 0.67247 0.52250 -3.3808 10.9164 -5.72342 41 -10.7076 -8.8012 0.60241 0.41924 1.60640 -1.50690 2.8396 3.1610 4.52694 42 4.0509 3.2867 -0.24823 0.75575 1.16079 0.58183 -0.9086 -2.9358 -5.76434 43 13.9942 0.0735 -1.48803 0.47383 0.29931 1.39587 -6.2020 2.5917 -9.67137 44 26.1745 -7.1785 -0.22644 3.31530 2.21891 -0.22341 -22.6706 -9.5371 7.08929 45 -3.2572 -4.4020 3.57914 -1.09963 -0.21863 0.45880 6.5896 5.4737 6.46936

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Obs PCO4 PCO5 PCO6 Temp1 Temp2 Oz1 Oz2

37 -2.92322 -8.03281 -0.14906 -0.20604 1.72848 -0.25841 1.65796 38 2.61135 -0.53264 -2.01203 -0.25597 -0.42891 0.03604 -1.33859 39 -0.45485 1.38336 -0.04074 -0.39640 -0.57928 -0.38387 -0.60707 40 -1.56727 -1.39724 -0.75400 1.00791 -0.36609 1.54585 -0.06878 41 0.11684 -2.75202 -0.49262 -0.25252 1.19375 -0.11585 0.91336 42 -0.29166 -0.10300 -0.30083 -0.23005 -0.45933 0.08801 -1.05299 43 -1.50718 -1.65827 0.03661 0.79508 -1.12682 1.18213 -1.35086 44 -3.23677 -0.72945 -3.23226 0.79146 -0.21567 0.85495 -0.58800 45 4.11503 3.17868 -0.60085 -0.27025 1.37060 -0.59559 1.67208

18:24 Saturday, November 21, 2009 211 Canonical Correlation using Monthly Means

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

46 Nashville 0 38.7793 317.780 28.4265 68.083 62.8333 67.9032 76.8000 47 New York 1 23.5229 349.159 31.2145 54.838 53.0889 62.6237 73.0778 48 Oakland 1 32.9006 257.387 11.4286 44.468 54.8000 55.6774 59.8333 49 Oklahoma City 0 50.8746 383.376 33.1593 84.337 61.5333 68.3226 75.9000 50 Omaha 0 52.4176 272.442 25.0224 78.087 51.5556 62.2581 70.8222 51 Philadelphia 0 36.3085 374.485 31.4981 67.873 53.8000 64.1613 73.1000 52 Phoenix 0 46.5798 256.498 24.3478 71.416 66.1333 80.0323 89.1333 53 Pittsburgh 0 54.4604 472.666 39.9480 94.720 52.1000 61.2581 69.6000 54 Riverside 1 49.7610 301.931 9.9004 59.726 62.9714 73.6037 79.1238

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

46 82.1935 79.6129 72.0333 5.99371 8.8557 10.2495 5.6462 11.4303 5.24058 47 80.8710 75.8495 69.5667 -0.85701 0.3905 7.4703 15.8371 6.1029 -3.16514 48 62.1935 64.0968 63.8667 9.22982 8.3519 0.9472 1.2300 -2.9679 0.55751 49 82.4194 84.9677 71.3667 5.96884 11.1463 2.9474 6.2657 20.3420 5.51697 50 80.6882 73.3548 64.0889 -0.40624 0.8112 -0.8071 4.5477 -1.0881 6.44135 51 81.3871 77.7097 70.1667 7.16699 10.1299 10.4305 18.1820 10.9228 -1.09160 52 91.4516 93.2258 87.6333 7.66572 11.8096 8.4950 8.8198 9.5064 -0.63484 53 76.2581 69.1935 64.4000 -0.36179 4.9377 10.6607 14.6198 2.4950 -2.82014 54 85.4378 84.6636 80.8048 5.01962 14.2865 15.4135 8.7508 8.3247 3.63020

Obs PCT1 PCT2 PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3

46 5.8323 0.6114 -1.73999 0.37610 0.55476 1.33427 3.8009 8.7095 1.16876 47 -5.7684 4.4769 0.92631 -0.92266 1.12864 1.14216 10.7296 -4.5476 -5.45988 48 -25.2487 -14.5940 0.94750 -1.37670 -0.24769 0.26326 -6.6838 -3.6423 8.40027 49 7.1021 2.5404 -3.02967 -4.12054 -0.32964 -0.62708 1.5254 15.8851 -3.98917 50 -10.8258 4.7645 -2.58624 0.82901 1.04203 -0.51962 -5.3588 -4.2429 -2.13502 51 -3.5652 4.6440 0.68634 -1.73091 1.10180 -0.02564 14.5383 5.3173 2.58508 52 31.8025 9.1449 6.40235 -1.95176 -0.93171 -0.48222 6.0155 5.3737 3.75061 53 -14.3237 0.2579 -0.75469 2.47868 0.18815 0.17283 11.4396 -5.4071 -0.65916 54 15.6944 3.2134 4.19679 -1.40090 1.73116 -1.32440 9.6475 6.9283 5.37257

Obs PCO4 PCO5 PCO6 Temp1 Temp2 Oz1 Oz2

46 0.43454 -2.56988 2.53244 0.43782 -1.17022 0.31702 0.95446 47 -0.47042 5.22026 2.61763 -0.58892 0.04545 -0.95222 -0.72274 48 -1.07375 1.88886 -0.47672 -0.06199 0.89199 -0.08518 0.64059 49 -4.60275 1.28898 -1.32890 1.69547 0.22718 1.80484 0.64951 50 7.51995 5.71575 0.11469 -0.58154 -0.89602 -0.51086 -0.47995 51 -4.49546 3.86432 0.07830 -0.27251 0.67427 -0.32803 1.11751 52 -4.85954 -0.84859 -0.50155 0.17286 2.53231 0.28121 0.95329 53 0.88714 1.38037 0.41721 -1.11114 -0.99668 -1.32215 -0.13991 54 1.04596 -6.08095 -0.82260 -0.08380 2.50876 -0.37816 1.51076

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18:24 Saturday, November 21, 2009 212 Canonical Correlation using Monthly Means

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

55 Sacramento 1 41.3568 274.214 17.8995 59.338 58.3267 64.2581 71.2067 56 San Antonio 1 29.1472 272.160 20.6758 49.967 71.4333 76.3548 82.0667 57 San Bernardino 1 43.1137 234.815 7.3124 50.602 59.2889 66.7957 71.2667 58 San Jose 1 26.6851 206.765 11.6487 38.453 54.8000 55.6774 59.8333 59 Santa Ana/Anaheim 1 29.6878 231.775 12.3670 42.301 58.8167 63.3871 65.6667 60 Shreveport 1 45.6529 352.098 27.9624 73.901 69.6333 72.1935 80.0333 61 St. Louis 0 39.9208 443.437 36.1872 76.682 58.8000 67.0323 75.0667 62 St. Petersburg 1 77.1583 483.894 32.4477 110.257 74.6000 78.0323 81.4000 63 Stockton 1 45.2450 324.345 13.1299 58.730 58.2222 64.5484 71.5667

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

55 73.6258 74.4387 73.2867 6.71122 7.9368 5.9901 7.9478 4.2798 8.03638 56 83.0968 86.4194 80.5667 6.96342 5.3762 -1.3773 -8.6641 2.1612 9.44449 57 76.7312 75.5054 72.8778 3.62120 12.9680 15.0344 8.3781 9.9923 1.10096 58 62.1935 64.0968 63.8667 8.75283 8.2189 -0.0051 1.6848 -3.9427 -1.07305 59 71.5161 70.0968 68.6000 9.37348 14.2964 10.1229 4.6612 6.4446 4.65991 60 83.1290 86.1290 75.5000 5.17327 6.0310 1.6275 -0.7434 13.2357 3.19671 61 83.1613 76.7419 69.9667 -0.48566 4.1664 1.4408 8.4464 5.2479 -1.96826 62 83.8065 84.0000 81.0333 9.64822 6.5928 -5.1627 -2.3514 -2.4759 1.15697 63 74.1183 74.5161 73.0222 7.35334 8.1715 5.1208 7.3916 2.5567 5.34866

Obs PCT1 PCT2 PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3

55 -4.2394 -4.9783 3.74576 -1.27013 -0.22150 0.59792 1.4839 4.7764 4.61654 56 22.3267 -2.4535 0.90105 -0.23864 -0.87394 -0.16114 -16.4055 3.5752 2.98679 57 -1.4824 -3.3776 2.19654 -0.28886 1.09281 -1.15253 9.8365 5.9869 2.59902 58 -25.2487 -14.5940 0.94750 -1.37670 -0.24769 0.26326 -6.7042 -5.4449 8.18470 59 -10.7076 -8.8012 0.60241 0.41924 1.60640 -1.50690 2.4676 7.3684 8.35770 60 16.7778 -1.2565 -2.92769 -1.70143 -0.59517 0.99968 -5.6794 7.8358 -3.67216 61 0.9640 2.9282 -1.49833 1.83419 1.57285 0.24228 1.5574 -3.2293 -4.45290 62 23.7667 -4.8977 0.36059 2.62399 0.91225 -0.52926 -13.2175 -3.3944 6.43732 63 -3.9697 -4.4348 3.48387 -0.96896 -0.30232 0.50115 0.6929 2.3165 5.60732

Obs PCO4 PCO5 PCO6 Temp1 Temp2 Oz1 Oz2

55 4.50366 2.99569 0.66529 -0.26958 1.42433 -0.28131 1.22994 56 4.48657 -1.15409 2.06987 1.12704 0.46810 0.91903 0.33787 57 -0.97958 -6.55217 -0.35848 -0.27952 1.54560 -0.20272 0.99957 58 -1.98515 2.48259 -1.17576 -0.06199 0.89199 -0.13469 0.44434 59 -0.32727 -3.69468 -0.64604 -0.25252 1.19375 0.14721 1.73089 60 -3.21430 -0.68288 1.97803 1.83769 -0.94244 1.42435 -0.13538 61 -1.50728 3.74971 -1.55604 -0.39042 -0.95013 -0.03763 -0.81622 62 -2.08913 4.39267 -0.82873 0.67101 0.03199 0.56854 0.20518 63 2.52557 2.97186 0.27293 -0.30675 1.27440 -0.30251 1.08221

18:24 Saturday, November 21, 2009 213 Canonical Correlation using Monthly Means

Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June

64 Syracuse 1 53.7047 326.410 30.3740 85.179 46.8333 60.9032 69.9667 65 Tacoma 1 42.6643 271.254 18.9778 62.070 48.7667 52.0968 58.3333 66 Tampa 1 51.8546 302.518 14.9157 67.171 74.6000 78.0323 81.4000 67 Toledo 0 55.8176 391.162 23.5137 79.331 50.9000 62.8387 71.0333 68 Washington 0 24.8226 323.218 21.1517 45.974 53.1667 63.0000 71.1000 69 Wichita 0 46.3710 269.394 18.7692 65.361 56.2000 65.4516 73.3000 70 Worcester 1 46.2073 306.806 38.0844 84.558 47.3889 58.7312 68.9111

Page 120: R Code for Calculating Beale’s F-Type Statistic: c1

Temp Obs July TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep

64 75.1613 69.0968 65.1000 1.04130 6.9690 12.5221 12.5066 -0.1769 1.07085 65 62.6774 65.0323 61.0333 7.19013 5.7665 -1.5010 -0.3845 -3.4556 -0.79503 66 83.8065 84.0000 81.0333 9.92602 7.3299 -4.6847 -3.0803 -2.3865 1.71172 67 77.4516 69.9677 65.3333 -5.91671 -1.5588 9.1269 8.0693 -0.3838 -3.32774 68 78.6774 75.6774 67.3333 2.21860 10.2754 12.0268 19.8456 16.1971 1.98466 69 82.5161 81.4839 67.2333 5.00061 10.3495 0.0144 9.1460 16.5816 3.67709 70 73.3978 69.3441 65.3778 6.90519 2.5181 8.5516 7.6622 -1.8237 -7.10564

Obs PCT1 PCT2 PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3

64 -17.1308 2.9873 2.38512 1.54375 -1.48368 -0.74559 9.8854 -4.1569 3.30174 65 -31.0113 -10.2201 0.51165 -4.20481 -0.53502 0.23984 -9.1854 -6.0976 5.46470 66 23.7667 -4.8977 0.36059 2.62399 0.91225 -0.52926 -13.5469 -2.7011 7.02300 67 -12.7102 2.2801 0.30406 2.89350 -0.35859 -0.60385 5.2271 -11.1895 -6.33434 68 -7.8689 2.6066 -0.55070 -1.41855 0.27215 -0.53623 17.6173 9.4381 -2.92259 69 -0.9229 5.0344 -3.81144 -3.24835 0.30498 -1.16001 1.8784 11.4890 -3.67853 70 -18.4321 1.2279 2.51117 -0.19154 -1.38912 0.50488 3.7933 -9.3615 4.59821

Obs PCO4 PCO5 PCO6 Temp1 Temp2 Oz1 Oz2

64 4.47144 -0.56280 0.29876 -1.68142 0.35830 -1.55764 0.53260 65 -1.37489 2.55729 -0.21078 0.14116 1.28945 0.02343 -0.02560 66 -1.83322 3.56576 -0.94951 0.67101 0.03199 0.60923 0.32644 67 4.09184 -0.98073 3.02210 -1.42775 -0.55076 -1.46163 -1.47791 68 -1.80935 2.65189 -1.19662 -0.12211 0.33978 -0.15314 0.85263 69 -4.63067 4.86440 -3.24336 1.06735 -0.04948 1.44561 0.39038 70 -3.98278 0.77403 5.18281 -1.25436 0.37403 -1.06255 -0.10731

18:24 Saturday, November 21, 2009 214 Canonical Correlation using Monthly Means

Plot of Temp1*Oz1. Legend: A = 1 obs, B = 2 obs, etc.

Temp1 ‚ ‚ 2.0 ˆ ‚ ‚ A A ‚ A A A ‚ A 1.5 ˆ A A A ‚ AA ‚ ‚ A ‚ A A 1.0 ˆ A ‚ A ‚ A A A ‚ B ‚ A 0.5 ˆ ‚ A ‚ ‚ AA A ‚ A A 0.0 ˆ A ‚ A BB ‚ A A A ‚ A BA AA A A ‚ AA A -0.5 ˆ A ‚ A A A ‚ B A ‚

Page 121: R Code for Calculating Beale’s F-Type Statistic: c1

‚ -1.0 ˆ A A A ‚ A ‚ A A ‚ A A ‚ A A A A -1.5 ˆ ‚ A ‚ A ‚ A ‚ -2.0 ˆ ‚ Šˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒƒƒˆ -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Oz1

18:24 Saturday, November 21, 2009 215 Canonical Correlation using PCs

The CANCORR Procedure

VAR Variables 2 WITH Variables 4 Observations 70

Means and Standard Deviations

Standard Variable Mean Deviation

PCT1 0 15.509597 PCT2 0 4.706717 PCO1 0 9.561405 PCO2 0 7.569826 PCO3 0 5.437974 PCO4 0 3.523088

18:24 Saturday, November 21, 2009 216 Canonical Correlation using PCs

The CANCORR Procedure

Correlations Among the Original Variables

Correlations Among the VAR Variables

PCT1 PCT2

PCT1 1.0000 0.0000 PCT2 0.0000 1.0000

Correlations Among the WITH Variables

PCO1 PCO2 PCO3 PCO4

PCO1 1.0000 0.0000 0.0000 0.0000 PCO2 0.0000 1.0000 0.0000 0.0000 PCO3 0.0000 0.0000 1.0000 0.0000 PCO4 0.0000 0.0000 0.0000 1.0000

Correlations Between the VAR Variables and the WITH Variables

PCO1 PCO2 PCO3 PCO4

PCT1 -0.5114 0.4803 -0.1308 -0.0252 PCT2 0.5174 -0.0443 -0.3018 -0.0665

Page 122: R Code for Calculating Beale’s F-Type Statistic: c1

18:24 Saturday, November 21, 2009 217 Canonical Correlation using PCs

The CANCORR Procedure

Canonical Correlation Analysis

Adjusted Approximate Squared Canonical Canonical Standard Canonical Correlation Correlation Error Correlation

1 0.832364 0.822933 0.036979 0.692830 2 0.427081 0.404912 0.098428 0.182398

Test of H0: The canonical correlations in the current row and all Eigenvalues of Inv(E)*H that follow are zero = CanRsq/(1-CanRsq) Likelihood Approximate Eigenvalue Difference Proportion Cumulative Ratio F Value Num DF Den DF Pr > F

1 2.2555 2.0324 0.9100 0.9100 0.25114235 15.93 8 128 <.0001 2 0.2231 0.0900 1.0000 0.81760164 4.83 3 65 0.0042

Multivariate Statistics and F Approximations

S=2 M=0.5 N=31

Statistic Value F Value Num DF Den DF Pr > F

Wilks' Lambda 0.25114235 15.93 8 128 <.0001 Pillai's Trace 0.87522879 12.64 8 130 <.0001 Hotelling-Lawley Trace 2.47862029 19.65 8 89.135 <.0001 Roy's Greatest Root 2.25553076 36.65 4 65 <.0001

NOTE: F Statistic for Roy's Greatest Root is an upper bound. NOTE: F Statistic for Wilks' Lambda is exact.

18:24 Saturday, November 21, 2009 218 Canonical Correlation using PCs

The CANCORR Procedure

Canonical Correlation Analysis

Raw Canonical Coefficients for the VAR Variables

PCTemp1 PCTemp2

PCT1 -0.051656174 0.0385852445 PCT2 0.1271462963 0.170217691

Raw Canonical Coefficients for the WITH Variables

PCOz1 PCOz2

PCO1 0.0903925413 0.0265631367 PCO2 -0.065277284 0.0779403879 PCO3 -0.01674661 -0.137831427 PCO4 -0.006687987 -0.045426673

18:24 Saturday, November 21, 2009 219 Canonical Correlation using PCs

The CANCORR Procedure

Page 123: R Code for Calculating Beale’s F-Type Statistic: c1

Canonical Correlation Analysis

Standardized Canonical Coefficients for the VAR Variables

PCTemp1 PCTemp2

PCT1 -0.8012 0.5984 PCT2 0.5984 0.8012

Standardized Canonical Coefficients for the WITH Variables

PCOz1 PCOz2

PCO1 0.8643 0.2540 PCO2 -0.4941 0.5900 PCO3 -0.0911 -0.7495 PCO4 -0.0236 -0.1600

18:24 Saturday, November 21, 2009 220 Canonical Correlation using PCs

The CANCORR Procedure

Canonical Structure

Correlations Between the VAR Variables and Their Canonical Variables

PCTemp1 PCTemp2

PCT1 -0.8012 0.5984 PCT2 0.5984 0.8012

Correlations Between the WITH Variables and Their Canonical Variables

PCOz1 PCOz2

PCO1 0.8643 0.2540 PCO2 -0.4941 0.5900 PCO3 -0.0911 -0.7495 PCO4 -0.0236 -0.1600

Correlations Between the VAR Variables and the Canonical Variables of the WITH Variables

PCOz1 PCOz2

PCT1 -0.6669 0.2556 PCT2 0.4981 0.3422

Correlations Between the WITH Variables and the Canonical Variables of the VAR Variables

PCTemp1 PCTemp2

PCO1 0.7194 0.1085 PCO2 -0.4113 0.2520 PCO3 -0.0758 -0.3201 PCO4 -0.0196 -0.0684

18:24 Saturday, November 21, 2009 221 Canonical Correlation using PCs

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July

1 Akron 0 64.2845 336.711 32.4186 97.2557 51.4000 61.6129 70.0667 76.0968 2 Arlington 1 15.8351 160.462 16.8907 32.7258 56.7667 67.4839 74.9333 83.2258 3 Atlanta 1 21.5268 206.496 21.3919 42.9862 65.3667 69.1290 75.1667 79.3871 4 Austin 1 34.7171 161.644 12.1879 47.3974 72.0000 76.6452 81.9667 83.4516 5 Bakersfield 1 47.6086 289.430 19.0434 66.9543 58.0667 66.6452 73.9000 80.2258 6 Baton Rouge 1 22.2840 370.108 19.8618 42.1459 72.0333 74.7419 80.5000 81.8710

Page 124: R Code for Calculating Beale’s F-Type Statistic: c1

7 Boston 1 29.5735 242.242 29.4285 59.1470 49.4000 58.4194 71.2000 76.0323 8 Buffalo 1 42.5145 427.039 31.8858 74.8212 46.1333 59.8387 68.5667 74.5806 9 Charlotte 1 31.7778 216.549 28.7582 60.8236 62.2333 65.9677 73.6333 79.0645

Obs TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2

1 68.4516 63.7333 -2.59742 2.9776 9.3160 10.1753 -1.3167 -5.4473 -14.9869 0.6743 2 79.9032 70.2667 -5.77401 3.3453 6.7535 13.4359 8.1736 -6.5235 1.5472 4.8813 3 82.1290 73.3000 -4.00079 2.8535 -1.9897 -0.0305 13.6344 2.2994 7.8431 -3.0030 4 88.5161 81.6667 8.26811 2.1398 -5.5971 -11.3581 9.2746 11.6430 24.1355 -2.3152 5 77.8710 77.2333 2.01369 10.1284 14.0376 13.9645 9.5357 16.2752 2.5044 0.4868 6 85.2903 76.3000 4.48913 13.4318 0.1609 -3.6472 8.2088 3.4473 18.8700 -3.8101 7 71.6452 67.3667 6.72094 2.6733 7.3469 7.7088 3.5155 -3.5027 -14.1691 2.6226 8 68.0645 64.4667 2.51458 9.0380 13.3186 15.9207 1.0480 0.3954 -19.3166 2.4911 9 79.6774 69.3667 0.53066 2.7441 4.2031 3.6292 12.7265 -6.9343 1.6325 -1.6437

Obs PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

1 -0.74777 3.34990 -0.46525 -0.06240 7.2086 -10.7570 -1.7173 0.9151 -0.65715 0.61300 2 -1.07394 -0.88940 0.67658 -1.13189 10.2075 -5.3432 -9.3266 -2.8348 1.24694 -1.56791 3 -1.72760 -2.23032 -0.07069 -0.11761 -6.1692 3.9501 -12.4227 -0.8587 0.44206 -1.19877 4 1.03536 -1.88439 -0.61332 -0.41074 -20.7477 9.3629 -1.9257 2.5538 1.23829 4.66429 5 5.21203 -1.45462 2.30347 0.42333 10.9585 12.3735 2.1102 12.4493 0.56094 -0.04786 6 -2.61150 0.00562 -1.30199 0.00649 -8.7079 6.3426 1.2839 -2.4453 -3.69869 -4.76767 7 2.33049 -0.90634 -0.53725 2.55027 3.3409 -3.5435 1.8472 -3.3435 1.75667 5.12471 8 2.34841 1.39937 -0.90051 -0.76557 13.2850 -2.6556 4.7551 2.8961 0.56255 -0.71447 9 -3.36313 -1.80680 -0.02224 0.57017 1.0243 -0.3890 -8.4562 -8.1418 -1.55721 2.67765

Obs Temp1 Temp2 Oz1 Oz2 PCTemp1 PCTemp2 PCOz1 PCOz2

1 -1.32495 -1.22142 -1.43513 -0.86124 0.85990 -0.46349 1.37643 -0.45180 2 0.10936 0.30195 -0.51418 -1.46566 0.54071 0.89058 1.44662 1.26896 3 1.39347 0.16513 1.38627 -1.56997 -0.78696 -0.20853 -0.60172 1.89524 4 1.53319 1.08099 2.00378 -0.00750 -1.54112 0.53718 -2.47146 0.32804 5 -0.72273 2.22521 -0.83176 1.98181 -0.06747 0.17950 0.06426 0.39910 6 1.69196 -0.85869 1.42646 0.28483 -1.45919 0.07956 -1.20631 0.19716 7 -0.99985 -0.29346 -0.47747 0.00535 1.06537 -0.10031 0.52473 -0.29015 8 -1.75035 0.47834 -1.57811 0.91275 1.31455 -0.32132 1.27521 -0.64105 9 1.23212 -0.83973 0.83888 -1.40342 -0.29332 -0.21680 0.31404 1.53228

18:24 Saturday, November 21, 2009 222 Canonical Correlation using PCs

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July

10 Chicago 0 33.0126 328.191 31.1527 64.5372 49.8000 61.8710 70.5667 78.5806 11 Cincinnati 0 53.2828 352.704 32.5355 85.8184 55.3000 63.7742 73.2667 79.1935 12 Cleveland 0 38.3076 427.984 24.1754 62.9135 50.5667 61.2581 70.4000 76.4194 13 Colorado Springs 0 43.7197 170.430 17.0236 62.0975 42.5333 53.4839 63.0333 71.3226 14 ColumbusGA 1 47.7747 654.889 30.5973 78.3720 68.2667 71.8548 78.3667 82.0323 15 ColumbusOH 0 39.9447 273.252 19.6449 59.8703 55.1667 65.0323 74.7333 80.3548 16 Corpus Christi 1 39.8540 256.660 23.5936 63.4475 74.9000 78.8387 82.9667 82.9355 17 Dallas/Fort Worth 1 30.9771 216.197 15.8576 46.9062 68.2833 73.8871 82.1167 86.0484 18 Dayton 0 48.6529 348.441 31.3024 81.7441 53.8333 63.8065 72.7333 78.6452

Obs TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2

10 70.5484 63.6667 1.25153 6.0385 7.6226 7.0373 -0.5158 0.0429 -13.9503 3.9212 11 72.9677 67.0667 -3.08945 3.1260 4.7007 5.7707 0.9676 -4.9646 -6.7571 1.6912 12 69.3548 65.1667 -4.30625 3.4514 9.1086 9.1632 0.2957 -4.3639 -14.4028 1.5558 13 69.0323 57.9000 8.53664 8.9151 5.4381 5.8312 2.1564 -2.5394 -28.9930 2.1174 14 84.3387 75.0833 -2.64460 2.9716 -2.1978 -5.9310 7.2687 6.1511 14.0706 -1.9498 15 73.3226 68.1000 -3.24023 5.2574 14.5176 7.3581 2.5967 -7.1603 -4.8662 2.9176 16 84.3871 79.8000 5.98796 4.8851 -5.2161 -13.0445 -5.0587 7.7383 24.2833 -4.9156

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17 90.2097 79.2667 3.47606 5.2499 1.2840 0.5819 19.9481 9.1287 21.6169 2.5418 18 71.5806 67.0000 -3.47475 2.9661 8.3600 8.3384 0.7234 -3.7851 -8.4739 1.8203

Obs PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

10 -1.10673 2.26395 0.01041 -0.60606 2.8437 -5.1358 1.98571 2.58459 -0.53973 -0.10706 11 -0.99259 2.20802 -0.02399 0.88352 1.4708 -8.9052 -4.21064 -0.56718 -0.60910 -0.67099 12 0.53504 2.33898 -0.31330 0.24892 6.6177 -9.3242 -3.52887 1.64395 -1.67449 -0.24452 13 -1.88199 -3.78581 -1.16758 -0.67332 0.8275 -1.6260 6.13964 -4.20728 0.59353 0.46815 14 -2.17827 -1.26909 -0.23253 0.19199 -12.5384 1.9496 -7.87801 3.83149 -1.66113 -0.54652 15 -0.22757 2.96128 -0.22718 0.73986 9.1578 -8.1477 -2.53909 -1.11891 -7.17741 1.57135 16 -0.51262 3.16668 -1.16086 -0.57813 -22.6665 -3.0216 4.85090 5.33374 -1.29846 0.27451 17 -0.52100 -3.78982 -0.30191 0.44379 -4.7377 15.1845 -8.14898 -0.28154 0.71969 2.30924 18 -0.01526 2.88076 -0.08407 0.34482 5.3642 -8.5966 -3.49200 1.51693 -1.24442 0.37378

Obs Temp1 Temp2 Oz1 Oz2 PCTemp1 PCTemp2 PCOz1 PCOz2

10 -1.20631 -0.86168 -0.92325 0.01153 1.21919 0.12919 0.54176 -0.71585 11 -0.73137 -1.35763 -0.61515 -1.26746 0.56407 0.02715 0.78856 -0.04888 12 -1.37403 -0.67440 -1.23280 -1.00379 0.94180 -0.29091 1.25495 -0.13924 13 -0.16745 0.31354 -0.12137 0.60709 1.76688 -0.75829 0.10626 -0.75986 14 1.48881 -0.39767 1.08290 -1.18552 -0.97474 0.21103 -1.15434 0.73068 15 -1.02679 -1.29567 -1.17183 -0.85268 0.62233 0.30886 1.40966 0.00902 16 0.87985 -0.65335 0.70728 -0.10422 -1.87939 0.10025 -1.96855 -1.74850 17 1.81658 0.56940 1.91418 -0.01627 -0.79346 1.26676 -1.28111 2.19361 18 -1.15503 -0.99399 -1.09088 -0.97304 0.66917 -0.01713 1.09438 -0.11514

18:24 Saturday, November 21, 2009 223 Canonical Correlation using PCs

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July

19 Denver 0 40.8828 205.978 22.1123 63.208 42.5917 54.3306 63.4167 73.1720 20 El Paso 1 29.8695 199.081 17.8040 47.968 63.4333 74.3548 80.2333 81.3226 21 Evansville 0 58.7476 588.639 31.4096 91.320 58.0000 65.6452 74.7667 79.6452 22 Fort Wayne 0 45.8040 288.686 23.2033 69.610 51.5000 62.5806 71.6333 78.6129 23 Fresno 1 35.6514 265.822 8.1310 44.158 58.7333 68.2258 76.2000 80.7097 24 Grand Rapids 0 35.8676 286.941 33.6041 70.690 49.0667 61.2258 69.5667 74.9032 25 Houston 1 21.0847 201.672 12.5567 33.877 73.1667 76.7742 82.1667 83.3226 26 Huntsville 1 29.9964 267.076 20.5999 50.596 65.7667 69.4194 76.4667 80.7419 27 Indianapolis 0 53.8088 322.272 26.2652 80.423 55.2667 64.5484 74.0000 79.5161

Obs TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2

19 70.6452 58.9889 6.96790 12.1597 8.0521 11.4697 6.8247 -1.1549 -26.8258 3.5811 20 81.4839 75.6667 9.70463 9.3137 7.6609 5.2615 5.6874 0.4456 12.1305 0.5803 21 74.6129 68.5000 -8.25527 1.0679 2.0634 2.7001 2.6426 -0.4325 -2.6194 0.8553 22 69.7419 64.5667 -4.89325 2.5078 6.7268 6.3050 -5.7237 -5.0256 -12.3593 2.8851 23 78.6452 77.4333 4.01151 12.9835 14.8018 16.4152 9.8696 13.5157 4.9179 1.2236 24 68.0000 62.9667 -3.30959 3.9831 8.5222 7.1289 -6.8933 -9.5720 -17.3701 1.2652 25 87.0968 78.1667 6.53232 6.4918 -4.4637 -7.1414 7.2114 8.3122 22.8477 -2.9608 26 80.8387 74.0333 3.96797 9.1020 6.4593 3.3874 15.2416 10.0658 8.7691 -2.3486 27 72.6129 67.2667 -6.14490 2.6241 4.6211 4.1704 -3.3937 -2.3107 -6.1580 2.0379

Obs PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

19 -1.70440 -4.40190 -0.36995 -1.10747 7.6369 2.9561 4.78068 -4.01867 0.83830 -1.98533 20 1.50494 1.77481 -2.54866 -1.73902 1.5689 3.0859 5.98163 -3.23107 -0.72043 2.11465 21 -1.19690 2.29236 -0.39411 0.86946 -2.4794 -7.3144 -9.72390 4.00459 -0.86949 -1.74390 22 -0.78728 3.62074 -0.00792 0.06092 2.2770 -14.5103 -1.77495 3.16558 -1.47916 -1.00664 23 5.08306 -0.56716 0.91284 0.44559 13.8210 12.5074 4.47701 9.17368 0.71421 -1.42310 24 -0.06601 2.97193 -1.44123 -0.74919 4.4709 -16.9083 0.47614 -0.44865 -2.86869 -1.01336 25 -2.02331 0.03371 -1.38042 -0.38197 -15.9398 6.7619 -0.19600 1.05549 0.79779 0.07555 26 -1.19596 -0.41012 0.47917 0.77058 -0.0968 13.5705 -2.47553 2.67415 -1.55364 0.71884

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27 -0.70043 3.06848 -0.30145 0.72111 -0.5302 -11.6557 -4.03534 4.36755 -1.48804 -1.89348

Obs Temp1 Temp2 Oz1 Oz2 PCTemp1 PCTemp2 PCOz1 PCOz2

19 -0.11244 0.78662 -0.11090 0.98946 1.84104 -0.42552 0.44417 -0.04311 20 -0.00245 0.46940 0.10826 1.00251 -0.55284 0.56683 -0.13818 -0.39549 21 -0.44291 -1.44996 -0.31588 -1.87074 0.24405 0.04451 0.38940 0.52239 22 -1.43265 -1.35583 -1.53951 -1.26278 1.00527 0.01421 1.16157 -0.96961 23 -0.74166 1.74224 -0.81847 2.29438 -0.09847 0.39803 0.29654 0.30816 24 -1.44984 -0.76180 -1.69460 -1.21422 1.05814 -0.45486 1.50289 -1.24433 25 1.70595 -0.52735 1.61670 0.09095 -1.55668 0.37761 -1.88602 0.08268 26 0.84326 -0.45198 1.01853 0.81123 -0.75159 -0.06142 -0.87103 1.27485 27 -0.95978 -1.45894 -1.08075 -1.38930 0.57720 0.10927 0.75129 -0.56474

18:24 Saturday, November 21, 2009 224 Canonical Correlation using PCs

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July

28 Jackson 1 31.8979 438.596 30.3030 62.201 69.5000 71.7742 79.7000 82.1935 29 Jersey City 1 28.0800 278.665 16.9137 44.994 53.5667 63.5484 74.3667 81.0968 30 Johnstown 0 55.0466 706.431 30.7999 86.502 47.8000 60.3226 69.7667 76.0000 31 Kansas CityKS 0 41.8034 261.588 25.3354 67.139 53.6667 64.3387 72.6167 82.0000 32 Kansas CityMO 0 50.7304 310.738 29.3645 80.424 54.8000 63.6452 71.7667 81.1613 33 Kingston 1 46.6951 738.682 18.5655 66.948 53.0889 62.6237 73.0778 80.8710 34 Knoxville 0 53.1369 305.210 29.5787 83.239 61.4000 66.3871 75.1333 78.8387 35 Lafayette 1 27.2962 262.988 23.0967 50.393 73.4000 76.9032 81.5667 82.5161 36 Lake Charles 1 34.8628 326.838 31.0496 65.912 72.2333 75.1290 80.7000 82.5484

Obs TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2

28 84.2258 75.3667 0.10213 3.5189 -2.0668 -5.8030 10.5212 1.56816 15.2773 -2.2649 29 76.5484 69.5333 4.06688 5.1239 11.9726 21.1476 9.2866 -2.58669 -4.3017 4.8683 30 69.0968 64.9333 0.84099 7.3021 5.8602 10.3271 -1.5896 -6.29763 -16.7821 2.8679 31 77.8871 65.8167 4.28449 10.5564 7.0183 11.9288 8.9702 1.99419 -5.1993 5.5430 32 76.5484 65.9667 -1.13202 5.7234 0.9810 5.5242 3.4300 -3.16688 -5.9731 3.7010 33 75.8495 69.5667 8.25349 6.4617 7.5877 3.5178 -3.3418 -2.37853 -5.7684 4.4769 34 78.0000 70.1000 1.39910 5.3193 3.9502 -0.0561 7.6415 -0.05212 1.4423 -1.2235 35 85.7419 78.4333 6.51440 8.3299 -2.7520 -5.1370 5.5211 3.68539 22.0975 -4.1566 36 86.0968 77.8667 6.32986 3.9044 -6.4831 -12.5135 3.5228 6.41760 20.3618 -3.4715

Obs PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

28 -2.39000 -0.62519 -0.59535 1.32246 -11.4442 2.8106 -7.90446 -2.17045 -2.07024 0.60662 29 0.64120 -0.60070 0.23792 1.09247 17.6271 0.8821 -0.58602 -2.65441 5.28560 2.54378 30 1.58015 1.58502 -0.57091 -0.09434 5.4344 -9.2095 1.89886 -2.35340 1.10024 -2.68804 31 -3.10141 -1.18550 0.40062 -1.02463 7.3641 4.9395 1.23285 -1.24908 1.96741 -2.15609 32 -3.07946 -0.70748 1.06065 -0.43332 -0.7935 -4.8643 -3.59731 -2.00248 1.49907 -3.00209 33 0.92631 -0.92266 1.12864 1.14216 -0.7343 -6.2686 8.18332 -1.13214 -1.13959 2.85516 34 -1.82076 -0.05541 -0.79801 1.08190 -3.6708 0.7157 -3.50991 -1.63296 -2.75997 1.03117 35 -1.44665 0.79854 -1.15359 -0.54452 -12.7062 3.5520 1.37866 -1.84587 -0.34592 -1.19942 36 -1.68571 -0.50229 -0.72039 -0.00694 -21.6937 2.3094 -0.24743 0.77883 -0.50460 1.54554

Obs Temp1 Temp2 Oz1 Oz2 PCTemp1 PCTemp2 PCOz1 PCOz2

28 1.48789 -1.15363 1.53724 -1.27136 -1.07713 0.20396 -1.07105 1.10314 29 -0.50525 -0.23784 -1.00528 0.50788 0.84119 0.66268 1.56334 0.73834 30 -1.57573 -0.07074 -0.97792 -0.38746 1.23154 -0.15938 1.07634 -0.72825 31 0.22653 -0.42198 0.00092 0.75873 0.97335 0.74290 0.33093 0.46742 32 0.15334 -0.64750 0.03637 -0.95090 0.77912 0.39950 0.31943 0.18658 33 -0.58892 0.04545 -0.79860 0.54482 0.86720 0.53948 0.21335 -1.58457 34 0.56147 -1.11766 0.57418 -0.60817 -0.23006 -0.15260 -0.30883 0.51623 35 1.44836 -0.39794 1.32311 0.03371 -1.66997 0.14511 -1.39116 -0.16684 36 1.64004 -0.34208 1.63545 -0.46155 -1.49320 0.19476 -2.11276 -0.39753

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18:24 Saturday, November 21, 2009 225 Canonical Correlation using PCs

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July

37 Las Vegas 0 45.9381 254.913 19.9162 65.854 61.2000 75.5806 85.4667 88.4194 38 Lexington 0 41.8407 272.924 25.3347 67.175 56.7000 65.5161 73.6667 79.8065 39 Lincoln 0 39.1544 361.180 14.3833 53.538 51.0667 61.8710 70.4000 80.8387 40 Little Rock 0 74.4175 308.736 19.6418 94.059 65.6833 71.1129 78.9000 84.4677 41 Los Angeles 1 30.3803 265.544 14.2027 44.804 58.8167 63.3871 65.6667 71.5161 42 Louisville 0 64.0135 380.188 35.3227 99.480 59.5000 67.8065 76.5000 83.4839 43 Memphis 0 32.8701 356.000 26.1847 59.278 67.2667 71.4194 79.9000 83.9355 44 Miami 1 35.9019 340.691 26.0500 62.085 78.0000 78.8387 81.0667 84.1613 45 Modesto 1 44.9667 293.738 14.7652 60.179 58.5167 64.8226 71.7333 74.3387

Obs TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2

37 88.1935 81.9333 8.86449 15.7920 15.3006 5.3280 5.5927 -0.30987 20.7651 8.9284 38 75.9355 68.9333 -6.40648 3.4592 3.4754 5.2706 7.5647 1.01188 -2.9717 1.6754 39 74.1935 64.1333 3.05017 3.8878 0.5766 1.2496 -3.6920 -2.70199 -10.9795 5.2255 40 84.2097 75.1667 2.31853 8.3827 2.2919 0.9441 16.0051 5.43948 13.2797 1.4361 41 70.0968 68.6000 5.58612 10.9744 9.0467 5.5017 5.2416 2.43886 -10.7076 -8.8012 42 78.7742 72.2667 -1.95398 3.5216 3.0344 3.9898 5.7273 -1.20572 4.0509 3.2867 43 82.9032 75.4333 -2.24268 3.4254 0.2333 -1.4341 11.6956 1.00112 13.9942 0.0735 44 83.8065 82.1000 7.48433 7.7844 -8.5097 -12.2927 -8.1683 -2.35173 26.1745 -7.1785 45 74.9032 73.4167 7.20520 10.4089 8.5813 12.2299 4.5215 7.47960 -3.2572 -4.4020

Obs PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

37 5.02954 -1.17045 -1.40892 -0.36416 6.8617 4.4484 9.59601 -2.92322 -8.03281 -0.14906 38 -0.69926 0.61528 0.03219 -0.04752 0.7825 -1.7250 -9.51820 2.61135 -0.53264 -2.01203 39 -2.61839 -0.17325 1.22765 -0.65754 -6.1163 -9.0566 2.16021 -0.45485 1.38336 -0.04074 40 -1.54032 -1.07223 0.67247 0.52250 -3.3808 10.9164 -5.72342 -1.56727 -1.39724 -0.75400 41 0.60241 0.41924 1.60640 -1.50690 2.8396 3.1610 4.52694 0.11684 -2.75202 -0.49262 42 -0.24823 0.75575 1.16079 0.58183 -0.9086 -2.9358 -5.76434 -0.29166 -0.10300 -0.30083 43 -1.48803 0.47383 0.29931 1.39587 -6.2020 2.5917 -9.67137 -1.50718 -1.65827 0.03661 44 -0.22644 3.31530 2.21891 -0.22341 -22.6706 -9.5371 7.08929 -3.23677 -0.72945 -3.23226 45 3.57914 -1.09963 -0.21863 0.45880 6.5896 5.4737 6.46936 4.11503 3.17868 -0.60085

Obs Temp1 Temp2 Oz1 Oz2 PCTemp1 PCTemp2 PCOz1 PCOz2

37 -0.20604 1.72848 -0.25841 1.65796 0.06257 2.32099 0.18872 -0.66086 38 -0.25597 -0.42891 0.03604 -1.33859 0.36653 0.17052 0.32527 1.07962 39 -0.39640 -0.57928 -0.38387 -0.60707 1.23156 0.46582 0.00519 -1.14542 40 1.00791 -0.36609 1.54585 -0.06878 -0.50338 0.75685 -0.91186 1.62109 41 -0.25252 1.19375 -0.11585 0.91336 -0.56593 -1.91128 -0.02626 -0.30746 42 -0.23005 -0.45933 0.08801 -1.05299 0.20863 0.71575 0.20799 0.55481 43 0.79508 -1.12682 1.18213 -1.35086 -0.71353 0.55249 -0.55775 1.43874 44 0.79146 -0.21567 0.85495 -0.58800 -2.26479 -0.21195 -1.52378 -2.17562 45 -0.27025 1.37060 -0.59559 1.67208 -0.39144 -0.87497 0.10248 -0.47695

18:24 Saturday, November 21, 2009 226 Canonical Correlation using PCs

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July

46 Nashville 0 38.7793 317.780 28.4265 68.083 62.8333 67.9032 76.8000 82.1935 47 New York 1 23.5229 349.159 31.2145 54.838 53.0889 62.6237 73.0778 80.8710 48 Oakland 1 32.9006 257.387 11.4286 44.468 54.8000 55.6774 59.8333 62.1935 49 Oklahoma City 0 50.8746 383.376 33.1593 84.337 61.5333 68.3226 75.9000 82.4194 50 Omaha 0 52.4176 272.442 25.0224 78.087 51.5556 62.2581 70.8222 80.6882 51 Philadelphia 0 36.3085 374.485 31.4981 67.873 53.8000 64.1613 73.1000 81.3871 52 Phoenix 0 46.5798 256.498 24.3478 71.416 66.1333 80.0323 89.1333 91.4516

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53 Pittsburgh 0 54.4604 472.666 39.9480 94.720 52.1000 61.2581 69.6000 76.2581 54 Riverside 1 49.7610 301.931 9.9004 59.726 62.9714 73.6037 79.1238 85.4378

Obs TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2

46 79.6129 72.0333 5.99371 8.8557 10.2495 5.6462 11.4303 5.24058 5.8323 0.6114 47 75.8495 69.5667 -0.85701 0.3905 7.4703 15.8371 6.1029 -3.16514 -5.7684 4.4769 48 64.0968 63.8667 9.22982 8.3519 0.9472 1.2300 -2.9679 0.55751 -25.2487 -14.5940 49 84.9677 71.3667 5.96884 11.1463 2.9474 6.2657 20.3420 5.51697 7.1021 2.5404 50 73.3548 64.0889 -0.40624 0.8112 -0.8071 4.5477 -1.0881 6.44135 -10.8258 4.7645 51 77.7097 70.1667 7.16699 10.1299 10.4305 18.1820 10.9228 -1.09160 -3.5652 4.6440 52 93.2258 87.6333 7.66572 11.8096 8.4950 8.8198 9.5064 -0.63484 31.8025 9.1449 53 69.1935 64.4000 -0.36179 4.9377 10.6607 14.6198 2.4950 -2.82014 -14.3237 0.2579 54 84.6636 80.8048 5.01962 14.2865 15.4135 8.7508 8.3247 3.63020 15.6944 3.2134

Obs PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

46 -1.73999 0.37610 0.55476 1.33427 3.8009 8.7095 1.16876 0.43454 -2.56988 2.53244 47 0.92631 -0.92266 1.12864 1.14216 10.7296 -4.5476 -5.45988 -0.47042 5.22026 2.61763 48 0.94750 -1.37670 -0.24769 0.26326 -6.6838 -3.6423 8.40027 -1.07375 1.88886 -0.47672 49 -3.02967 -4.12054 -0.32964 -0.62708 1.5254 15.8851 -3.98917 -4.60275 1.28898 -1.32890 50 -2.58624 0.82901 1.04203 -0.51962 -5.3588 -4.2429 -2.13502 7.51995 5.71575 0.11469 51 0.68634 -1.73091 1.10180 -0.02564 14.5383 5.3173 2.58508 -4.49546 3.86432 0.07830 52 6.40235 -1.95176 -0.93171 -0.48222 6.0155 5.3737 3.75061 -4.85954 -0.84859 -0.50155 53 -0.75469 2.47868 0.18815 0.17283 11.4396 -5.4071 -0.65916 0.88714 1.38037 0.41721 54 4.19679 -1.40090 1.73116 -1.32440 9.6475 6.9283 5.37257 1.04596 -6.08095 -0.82260

Obs Temp1 Temp2 Oz1 Oz2 PCTemp1 PCTemp2 PCOz1 PCOz2

46 0.43782 -1.17022 0.31702 0.95446 -0.22354 0.32911 -0.24744 0.59895 47 -0.58892 0.04545 -0.95222 -0.72274 0.86720 0.53948 1.36131 0.70448 48 -0.06199 0.89199 -0.08518 0.64059 -0.55132 -3.45838 -0.49990 -1.57047 49 1.69547 0.22718 1.80484 0.64951 -0.04386 0.70646 -0.80146 2.03753 50 -0.58154 -0.89602 -0.51086 -0.47995 1.16500 0.39328 -0.22197 -0.52037 51 -0.27251 0.67427 -0.32803 1.11751 0.77464 0.65293 0.95383 0.64853 52 0.17286 2.53231 0.28121 0.95329 -0.48005 2.78374 0.16266 0.28242 53 -1.11114 -0.99668 -1.32215 -0.13991 0.77270 -0.50879 1.39212 -0.06701 54 -0.08380 2.50876 -0.37816 1.51076 -0.40215 1.15254 0.32284 0.00824

18:24 Saturday, November 21, 2009 227 Canonical Correlation using PCs

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July

55 Sacramento 1 41.3568 274.214 17.8995 59.338 58.3267 64.2581 71.2067 73.6258 56 San Antonio 1 29.1472 272.160 20.6758 49.967 71.4333 76.3548 82.0667 83.0968 57 San Bernardino 1 43.1137 234.815 7.3124 50.602 59.2889 66.7957 71.2667 76.7312 58 San Jose 1 26.6851 206.765 11.6487 38.453 54.8000 55.6774 59.8333 62.1935 59 Santa Ana/Anaheim 1 29.6878 231.775 12.3670 42.301 58.8167 63.3871 65.6667 71.5161 60 Shreveport 1 45.6529 352.098 27.9624 73.901 69.6333 72.1935 80.0333 83.1290 61 St. Louis 0 39.9208 443.437 36.1872 76.682 58.8000 67.0323 75.0667 83.1613 62 St. Petersburg 1 77.1583 483.894 32.4477 110.257 74.6000 78.0323 81.4000 83.8065 63 Stockton 1 45.2450 324.345 13.1299 58.730 58.2222 64.5484 71.5667 74.1183

Obs TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2

55 74.4387 73.2867 6.71122 7.9368 5.9901 7.9478 4.2798 8.03638 -4.2394 -4.9783 56 86.4194 80.5667 6.96342 5.3762 -1.3773 -8.6641 2.1612 9.44449 22.3267 -2.4535 57 75.5054 72.8778 3.62120 12.9680 15.0344 8.3781 9.9923 1.10096 -1.4824 -3.3776 58 64.0968 63.8667 8.75283 8.2189 -0.0051 1.6848 -3.9427 -1.07305 -25.2487 -14.5940 59 70.0968 68.6000 9.37348 14.2964 10.1229 4.6612 6.4446 4.65991 -10.7076 -8.8012 60 86.1290 75.5000 5.17327 6.0310 1.6275 -0.7434 13.2357 3.19671 16.7778 -1.2565 61 76.7419 69.9667 -0.48566 4.1664 1.4408 8.4464 5.2479 -1.96826 0.9640 2.9282 62 84.0000 81.0333 9.64822 6.5928 -5.1627 -2.3514 -2.4759 1.15697 23.7667 -4.8977

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63 74.5161 73.0222 7.35334 8.1715 5.1208 7.3916 2.5567 5.34866 -3.9697 -4.4348

Obs PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

55 3.74576 -1.27013 -0.22150 0.59792 1.4839 4.7764 4.61654 4.50366 2.99569 0.66529 56 0.90105 -0.23864 -0.87394 -0.16114 -16.4055 3.5752 2.98679 4.48657 -1.15409 2.06987 57 2.19654 -0.28886 1.09281 -1.15253 9.8365 5.9869 2.59902 -0.97958 -6.55217 -0.35848 58 0.94750 -1.37670 -0.24769 0.26326 -6.7042 -5.4449 8.18470 -1.98515 2.48259 -1.17576 59 0.60241 0.41924 1.60640 -1.50690 2.4676 7.3684 8.35770 -0.32727 -3.69468 -0.64604 60 -2.92769 -1.70143 -0.59517 0.99968 -5.6794 7.8358 -3.67216 -3.21430 -0.68288 1.97803 61 -1.49833 1.83419 1.57285 0.24228 1.5574 -3.2293 -4.45290 -1.50728 3.74971 -1.55604 62 0.36059 2.62399 0.91225 -0.52926 -13.2175 -3.3944 6.43732 -2.08913 4.39267 -0.82873 63 3.48387 -0.96896 -0.30232 0.50115 0.6929 2.3165 5.60732 2.52557 2.97186 0.27293

Obs Temp1 Temp2 Oz1 Oz2 PCTemp1 PCTemp2 PCOz1 PCOz2

55 -0.26958 1.42433 -0.28131 1.22994 -0.41398 -1.01097 -0.28509 -0.42920 56 1.12704 0.46810 0.91903 0.33787 -1.46526 0.44385 -1.79634 -0.77261 57 -0.27952 1.54560 -0.20272 0.99957 -0.35288 -0.63214 0.46136 0.41418 58 -0.06199 0.89199 -0.13469 0.44434 -0.55132 -3.45838 -0.37437 -1.64039 59 -0.25252 1.19375 0.14721 1.73089 -0.56593 -1.91128 -0.39571 -0.49724 60 1.83769 -0.94244 1.42435 -0.13538 -1.02644 0.43350 -0.94188 1.11202 61 -0.39042 -0.95013 -0.03763 -0.81622 0.32252 0.53564 0.43623 0.47190 62 0.67101 0.03199 0.56854 0.20518 -1.85042 0.08336 -1.06702 -1.40802 63 -0.30675 1.27440 -0.30251 1.08221 -0.35881 -0.90806 -0.19937 -0.68864

18:24 Saturday, November 21, 2009 228 Canonical Correlation using PCs

Temp Temp Temp Obs city coast newcopd newcvd newpneu newresp April TempMay June July

64 Syracuse 1 53.7047 326.410 30.3740 85.179 46.8333 60.9032 69.9667 75.1613 65 Tacoma 1 42.6643 271.254 18.9778 62.070 48.7667 52.0968 58.3333 62.6774 66 Tampa 1 51.8546 302.518 14.9157 67.171 74.6000 78.0323 81.4000 83.8065 67 Toledo 0 55.8176 391.162 23.5137 79.331 50.9000 62.8387 71.0333 77.4516 68 Washington 0 24.8226 323.218 21.1517 45.974 53.1667 63.0000 71.1000 78.6774 69 Wichita 0 46.3710 269.394 18.7692 65.361 56.2000 65.4516 73.3000 82.5161 70 Worcester 1 46.2073 306.806 38.0844 84.558 47.3889 58.7312 68.9111 73.3978

Obs TempAug TempSep O3April O3May O3June O3July O3Aug O3Sep PCT1 PCT2

64 69.0968 65.1000 1.04130 6.9690 12.5221 12.5066 -0.1769 1.07085 -17.1308 2.9873 65 65.0323 61.0333 7.19013 5.7665 -1.5010 -0.3845 -3.4556 -0.79503 -31.0113 -10.2201 66 84.0000 81.0333 9.92602 7.3299 -4.6847 -3.0803 -2.3865 1.71172 23.7667 -4.8977 67 69.9677 65.3333 -5.91671 -1.5588 9.1269 8.0693 -0.3838 -3.32774 -12.7102 2.2801 68 75.6774 67.3333 2.21860 10.2754 12.0268 19.8456 16.1971 1.98466 -7.8689 2.6066 69 81.4839 67.2333 5.00061 10.3495 0.0144 9.1460 16.5816 3.67709 -0.9229 5.0344 70 69.3441 65.3778 6.90519 2.5181 8.5516 7.6622 -1.8237 -7.10564 -18.4321 1.2279

Obs PCT3 PCT4 PCT5 PCT6 PCO1 PCO2 PCO3 PCO4 PCO5 PCO6

64 2.38512 1.54375 -1.48368 -0.74559 9.8854 -4.1569 3.30174 4.47144 -0.56280 0.29876 65 0.51165 -4.20481 -0.53502 0.23984 -9.1854 -6.0976 5.46470 -1.37489 2.55729 -0.21078 66 0.36059 2.62399 0.91225 -0.52926 -13.5469 -2.7011 7.02300 -1.83322 3.56576 -0.94951 67 0.30406 2.89350 -0.35859 -0.60385 5.2271 -11.1895 -6.33434 4.09184 -0.98073 3.02210 68 -0.55070 -1.41855 0.27215 -0.53623 17.6173 9.4381 -2.92259 -1.80935 2.65189 -1.19662 69 -3.81144 -3.24835 0.30498 -1.16001 1.8784 11.4890 -3.67853 -4.63067 4.86440 -3.24336 70 2.51117 -0.19154 -1.38912 0.50488 3.7933 -9.3615 4.59821 -3.98278 0.77403 5.18281

Obs Temp1 Temp2 Oz1 Oz2 PCTemp1 PCTemp2 PCOz1 PCOz2

64 -1.68142 0.35830 -1.55764 0.53260 1.26474 -0.15250 1.07972 -0.71961 65 0.14116 1.28945 0.02343 -0.02560 0.30248 -2.93622 -0.51458 -1.41000

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66 0.67101 0.03199 0.60923 0.32644 -1.85042 0.08336 -1.15357 -1.45509 67 -1.42775 -0.55076 -1.46163 -1.47791 0.94647 -0.10231 1.28162 -0.04608 68 -0.12211 0.33978 -0.15314 0.85263 0.73790 0.14006 1.03742 1.68859 69 1.06735 -0.04948 1.44561 0.39038 0.68777 0.82133 -0.48761 1.66273 70 -1.25436 0.37403 -1.06255 -0.10731 1.10826 -0.50219 0.90361 -1.08173

18:24 Saturday, November 21, 2009 229 Canonical Correlation using PCs

Plot of PCTemp1*PCOz1. Legend: A = 1 obs, B = 2 obs, etc.

PCTemp1 ‚ ‚ 2 ˆ ‚ A ‚ A ‚ ‚ ‚ A A B A ‚ A A 1 ˆ A A A B A ‚ A B A ‚ A A A AA A ‚ B AA ‚ A ‚ A AA ‚ A 0 ˆ A A A ‚ A ‚ A A A A ‚ AA AA A ‚ A A B A A ‚ A A ‚ A A -1 ˆ A A ‚ A ‚ ‚ A A A ‚ A A ‚ A ‚ A A A -2 ˆ ‚ ‚ A ‚ ‚ ‚ ‚ -3 ˆ ‚ Šƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒ -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

PCOz1

18:24 Saturday, November 21, 2009 230 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 6 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Page 131: R Code for Calculating Beale’s F-Type Statistic: c1

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

Pooled Covariance Matrix Information

Natural Log of the Covariance Determinant of the Matrix Rank Covariance Matrix

6 10.49675

18:24 Saturday, November 21, 2009 231 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure

Pairwise Generalized Squared Distances Between Groups

2 _ _ -1 _ _ D (i|j) = (X - X )' COV (X - X ) i j i j

Generalized Squared Distance to coast

From coast 0 1

0 0 4.41495 1 4.41495 0

Linear Discriminant Function

_ -1 _ -1 _ Constant = -.5 X' COV X Coefficient Vector = COV X j j j

Linear Discriminant Function for coast

Variable 0 1

Constant -165.47097 -160.27862 TempApril 1.73444 1.81366 TempMay -5.54289 -5.69109 TempJune -2.10976 -2.23672 TempJuly 8.23011 7.65619 TempAug -2.62329 -2.47045 TempSep 4.23208 4.84195

18:24 Saturday, November 21, 2009 232 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Page 132: R Code for Calculating Beale’s F-Type Statistic: c1

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.9571 0.0429 2 1 0 * 0.9258 0.0742 3 1 1 0.0930 0.9070 4 1 1 0.0102 0.9898 5 1 1 0.0295 0.9705 6 1 1 0.1012 0.8988 7 1 0 * 0.5480 0.4520 8 1 0 * 0.8594 0.1406 9 1 1 0.4741 0.5259 10 0 0 0.9888 0.0112 11 0 0 0.9293 0.0707 12 0 0 0.9116 0.0884 13 0 0 0.9197 0.0803 14 1 1 0.1675 0.8325 15 0 0 0.9499 0.0501 16 1 1 0.0534 0.9466 17 1 1 0.1222 0.8778 18 0 0 0.9287 0.0713 19 0 0 0.9404 0.0596 20 1 1 0.2809 0.7191 21 0 0 0.8769 0.1231 22 0 0 0.9849 0.0151 23 1 1 0.0482 0.9518 24 0 0 0.9535 0.0465 25 1 1 0.0877 0.9123 26 1 1 0.1718 0.8282 27 0 0 0.9480 0.0520 28 1 1 0.1670 0.8330

18:24 Saturday, November 21, 2009 233 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.8653 0.1347 30 0 0 0.9067 0.0933 31 0 0 0.9870 0.0130 32 0 0 0.9749 0.0251 33 1 0 * 0.8256 0.1744 34 0 1 * 0.4737 0.5263 35 1 1 0.0554 0.9446 36 1 1 0.0570 0.9430 37 0 1 * 0.3337 0.6663 38 0 0 0.8226 0.1774 39 0 0 0.9919 0.0081 40 0 1 * 0.4813 0.5187 41 1 1 0.0259 0.9741

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42 0 0 0.8396 0.1604 43 0 1 * 0.4265 0.5735 44 1 1 0.0185 0.9815 45 1 1 0.0093 0.9907 46 0 0 0.6720 0.3280 47 1 0 * 0.8256 0.1744 48 1 1 0.0012 0.9988 49 0 0 0.6191 0.3809 50 0 0 0.9930 0.0070 51 0 0 0.7982 0.2018 52 0 1 * 0.0785 0.9215 53 0 0 0.9248 0.0752 54 1 1 0.0821 0.9179 55 1 1 0.0063 0.9937 56 1 1 0.0226 0.9774 57 1 1 0.0526 0.9474 58 1 1 0.0012 0.9988 59 1 1 0.0259 0.9741 60 1 1 0.2061 0.7939 61 0 0 0.9499 0.0501 62 1 1 0.0335 0.9665 63 1 1 0.0106 0.9894 64 1 0 * 0.8675 0.1325 65 1 1 0.0059 0.9941 66 1 1 0.0335 0.9665 67 0 0 0.9534 0.0466 68 0 0 0.8149 0.1851 69 0 0 0.9631 0.0369

18:24 Saturday, November 21, 2009 234 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 0 * 0.5400 0.4600

* Misclassified observation

18:24 Saturday, November 21, 2009 235 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Page 134: R Code for Calculating Beale’s F-Type Statistic: c1

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 27 5 32 84.38 15.63 100.00

1 8 30 38 21.05 78.95 100.00

Total 35 35 70 50.00 50.00 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1563 0.2105 0.1834 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 236 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.9529 0.0471 2 1 0 * 0.9608 0.0392 3 1 1 0.1006 0.8994 4 1 1 0.0102 0.9898 5 1 1 0.0337 0.9663 6 1 1 0.1181 0.8819 7 1 0 * 0.7690 0.2310 8 1 0 * 0.9218 0.0782 9 1 0 * 0.5372 0.4628 10 0 0 0.9885 0.0115 11 0 0 0.9230 0.0770 12 0 0 0.9039 0.0961 13 0 0 0.8906 0.1094 14 1 1 0.1826 0.8174 15 0 0 0.9452 0.0548 16 1 1 0.0630 0.9370 17 1 1 0.1479 0.8521 18 0 0 0.9227 0.0773 19 0 0 0.9201 0.0799

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20 1 1 0.4571 0.5429 21 0 0 0.8637 0.1363 22 0 0 0.9843 0.0157 23 1 1 0.0548 0.9452 24 0 0 0.9459 0.0541 25 1 1 0.1024 0.8976 26 1 1 0.1850 0.8150 27 0 0 0.9430 0.0570 28 1 1 0.2004 0.7996

18:24 Saturday, November 21, 2009 237 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.9104 0.0896 30 0 0 0.8971 0.1029 31 0 0 0.9866 0.0134 32 0 0 0.9731 0.0269 33 1 0 * 0.8927 0.1073 34 0 1 * 0.4085 0.5915 35 1 1 0.0623 0.9377 36 1 1 0.0620 0.9380 37 0 1 * 0.1160 0.8840 38 0 0 0.8189 0.1811 39 0 0 0.9920 0.0080 40 0 1 * 0.4291 0.5709 41 1 1 0.0285 0.9715 42 0 0 0.8228 0.1772 43 0 1 * 0.3379 0.6621 44 1 1 0.0192 0.9808 45 1 1 0.0091 0.9909 46 0 0 0.6186 0.3814 47 1 0 * 0.8927 0.1073 48 1 1 0.0006 0.9994 49 0 0 0.5007 0.4993 50 0 0 0.9931 0.0069 51 0 0 0.7720 0.2280 52 0 1 * 0.0036 0.9964 53 0 0 0.9186 0.0814 54 1 1 0.1113 0.8887 55 1 1 0.0059 0.9941 56 1 1 0.0236 0.9764 57 1 1 0.0584 0.9416 58 1 1 0.0006 0.9994 59 1 1 0.0285 0.9715 60 1 1 0.2499 0.7501 61 0 0 0.9441 0.0559 62 1 1 0.0368 0.9632 63 1 1 0.0106 0.9894 64 1 0 * 0.9374 0.0626 65 1 1 0.0046 0.9954 66 1 1 0.0368 0.9632 67 0 0 0.9490 0.0510 68 0 0 0.8025 0.1975 69 0 0 0.9562 0.0438

18:24 Saturday, November 21, 2009 238 Classification Analysis on Coast using Monthly Average Temperature

Page 136: R Code for Calculating Beale’s F-Type Statistic: c1

RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 0 * 0.6338 0.3662

* Misclassified observation

18:24 Saturday, November 21, 2009 239 Classification Analysis on Coast using Monthly Average Temperature RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 27 5 32 84.38 15.63 100.00

1 9 29 38 23.68 76.32 100.00

Total 36 34 70 51.43 48.57 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1563 0.2368 0.1965 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 240 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 6 DF Within Classes 68

Page 137: R Code for Calculating Beale’s F-Type Statistic: c1

Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

18:24 Saturday, November 21, 2009 241 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 0 * 0.8261 0.1739 3 1 1 0.0000 1.0000 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 1 0.0000 1.0000 7 1 1 0.0000 1.0000 8 1 0 * 0.6404 0.3596 9 1 1 0.0000 1.0000 10 0 0 1.0000 0.0000 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 0 1.0000 0.0000 14 1 1 0.0000 1.0000 15 0 0 1.0000 0.0000 16 1 1 0.0000 1.0000 17 1 1 0.2289 0.7711 18 0 0 1.0000 0.0000 19 0 0 1.0000 0.0000 20 1 1 0.0000 1.0000 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 0.6404 0.3596 25 1 1 0.0000 1.0000 26 1 0 * 0.6404 0.3596 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 242 Classification Analysis on Coast using

Page 138: R Code for Calculating Beale’s F-Type Statistic: c1

Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 1 0.4419 0.5581 29 1 1 0.4419 0.5581 30 0 0 0.6404 0.3596 31 0 0 0.8261 0.1739 32 0 0 0.8261 0.1739 33 1 1 0.4419 0.5581 34 0 1 * 0.4419 0.5581 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 1 * 0.4419 0.5581 38 0 0 1.0000 0.0000 39 0 0 0.8261 0.1739 40 0 0 0.6404 0.3596 41 1 1 0.0000 1.0000 42 0 0 0.6404 0.3596 43 0 0 0.6404 0.3596 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 0 0.8261 0.1739 47 1 1 0.4419 0.5581 48 1 1 0.0000 1.0000 49 0 0 0.6404 0.3596 50 0 0 1.0000 0.0000 51 0 0 0.6404 0.3596 52 0 1 * 0.4419 0.5581 53 0 0 1.0000 0.0000 54 1 1 0.2289 0.7711 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.0000 1.0000 58 1 1 0.0000 1.0000 59 1 1 0.0000 1.0000 60 1 1 0.2289 0.7711 61 0 0 1.0000 0.0000 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 0 * 0.6404 0.3596 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 1.0000 0.0000 68 0 0 0.8261 0.1739

18:24 Saturday, November 21, 2009 243 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 0.8261 0.1739

Page 139: R Code for Calculating Beale’s F-Type Statistic: c1

70 1 1 0.4419 0.5581

* Misclassified observation

18:24 Saturday, November 21, 2009 244 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 29 3 32 90.63 9.38 100.00

1 4 34 38 10.53 89.47 100.00

Total 33 37 70 47.14 52.86 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.0938 0.1053 0.0995 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 245 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Page 140: R Code for Calculating Beale’s F-Type Statistic: c1

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 0 * 1.0000 0.0000 3 1 1 0.0000 1.0000 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 1 0.0000 1.0000 7 1 1 0.2242 0.7758 8 1 0 * 0.8222 0.1778 9 1 1 0.2242 0.7758 10 0 0 1.0000 0.0000 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 0 1.0000 0.0000 14 1 1 0.0000 1.0000 15 0 0 1.0000 0.0000 16 1 1 0.0000 1.0000 17 1 1 0.2242 0.7758 18 0 0 1.0000 0.0000 19 0 0 1.0000 0.0000 20 1 1 0.2242 0.7758 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 0.6477 0.3523 25 1 1 0.0000 1.0000 26 1 0 * 0.6343 0.3657 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 246 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 1 0.4353 0.5647 29 1 0 * 0.6343 0.3657 30 0 0 0.6477 0.3523 31 0 0 0.8306 0.1694 32 0 0 0.8306 0.1694 33 1 0 * 0.6343 0.3657 34 0 1 * 0.4497 0.5503 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 1 * 0.2346 0.7654 38 0 0 1.0000 0.0000 39 0 0 0.8306 0.1694 40 0 0 0.6477 0.3523 41 1 1 0.0000 1.0000 42 0 0 0.6477 0.3523 43 0 0 0.6477 0.3523 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000

Page 141: R Code for Calculating Beale’s F-Type Statistic: c1

46 0 0 0.8306 0.1694 47 1 0 * 0.6343 0.3657 48 1 1 0.0000 1.0000 49 0 1 * 0.4497 0.5503 50 0 0 1.0000 0.0000 51 0 1 * 0.4497 0.5503 52 0 1 * 0.2346 0.7654 53 0 0 1.0000 0.0000 54 1 1 0.2242 0.7758 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.0000 1.0000 58 1 1 0.0000 1.0000 59 1 1 0.0000 1.0000 60 1 1 0.2242 0.7758 61 0 0 1.0000 0.0000 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 0 * 0.6343 0.3657 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 1.0000 0.0000 68 0 0 0.8306 0.1694

18:24 Saturday, November 21, 2009 247 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 0.8306 0.1694 70 1 1 0.4353 0.5647

* Misclassified observation

18:24 Saturday, November 21, 2009 248 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

Page 142: R Code for Calculating Beale’s F-Type Statistic: c1

0 27 5 32 84.38 15.63 100.00

1 7 31 38 18.42 81.58 100.00

Total 34 36 70 48.57 51.43 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1563 0.1842 0.1702 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 249 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The LOGISTIC Procedure

Model Information

Data Set WORK.PCCOMB Response Variable coast Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring

Number of Observations Read 70 Number of Observations Used 70

Response Profile

Ordered Total Value coast Frequency

1 0 32 2 1 38

Probability modeled is coast=0.

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

Model Fit Statistics

Intercept Intercept and Criterion Only Covariates

AIC 98.526 52.633 SC 100.774 68.372 -2 Log L 96.526 38.633

Testing Global Null Hypothesis: BETA=0

Page 143: R Code for Calculating Beale’s F-Type Statistic: c1

Test Chi-Square DF Pr > ChiSq

Likelihood Ratio 57.8930 6 <.0001 Score 37.1030 6 <.0001 Wald 12.0469 6 0.0609

18:24 Saturday, November 21, 2009 250 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

The LOGISTIC Procedure

Analysis of Maximum Likelihood Estimates

Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq

Intercept 1 -37.0462 14.4179 6.6021 0.0102 TempApril 1 -0.2165 0.1623 1.7791 0.1823 TempMay 1 0.2491 0.4558 0.2988 0.5846 TempJune 1 1.0680 0.8217 1.6892 0.1937 TempJuly 1 0.7725 0.3751 4.2401 0.0395 TempAug 1 0.0543 0.2272 0.0572 0.8109 TempSep 1 -1.5996 0.6347 6.3518 0.0117

Odds Ratio Estimates

Point 95% Wald Effect Estimate Confidence Limits

TempApril 0.805 0.586 1.107 TempMay 1.283 0.525 3.134 TempJune 2.909 0.581 14.563 TempJuly 2.165 1.038 4.516 TempAug 1.056 0.676 1.648 TempSep 0.202 0.058 0.701

Association of Predicted Probabilities and Observed Responses

Percent Concordant 95.0 Somers' D 0.900 Percent Discordant 5.0 Gamma 0.900 Percent Tied 0.0 Tau-a 0.453 Pairs 1216 c 0.950

18:24 Saturday, November 21, 2009 251 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

Obs coast predict phat Pcoast Pnoncoast

1 0 0 0.92811 0.07189 0.92811 2 1 0 0.97668 0.02332 0.97668 3 1 1 0.00568 0.99432 0.00568 4 1 1 0.00063 0.99937 0.00063 5 1 1 0.00001 0.99999 0.00001 6 1 1 0.09777 0.90223 0.09777 7 1 1 0.09259 0.90741 0.09259 8 1 1 0.32940 0.67060 0.32940 9 1 1 0.26853 0.73147 0.26853 10 0 0 0.99647 0.00353 0.99647 11 0 0 0.95144 0.04856 0.95144 12 0 0 0.73331 0.26669 0.73331 13 0 0 0.64926 0.35074 0.64926 14 1 1 0.08430 0.91570 0.08430 15 0 0 0.98444 0.01556 0.98444

Page 144: R Code for Calculating Beale’s F-Type Statistic: c1

16 1 1 0.01775 0.98225 0.01775 17 1 1 0.24086 0.75914 0.24086 18 0 0 0.91204 0.08796 0.91204 19 0 0 0.73067 0.26933 0.73067 20 1 1 0.41124 0.58876 0.41124 21 0 0 0.93112 0.06888 0.93112 22 0 0 0.99413 0.00587 0.99413 23 1 1 0.00018 0.99982 0.00018 24 0 0 0.93777 0.06223 0.93777 25 1 1 0.12479 0.87521 0.12479 26 1 1 0.01821 0.98179 0.01821 27 0 0 0.97953 0.02047 0.97953 28 1 1 0.17034 0.82966 0.17034 29 1 0 0.89916 0.10084 0.89916 30 0 0 0.67620 0.32380 0.67620 31 0 0 0.99926 0.00074 0.99926 32 0 0 0.99278 0.00722 0.99278 33 1 0 0.60319 0.39681 0.60319 34 0 1 0.36496 0.63504 0.36496 35 1 1 0.02343 0.97657 0.02343 36 1 1 0.01995 0.98005 0.01995 37 0 0 0.86314 0.13686 0.86314 38 0 0 0.76530 0.23470 0.76530 39 0 0 0.99832 0.00168 0.99832 40 0 0 0.57440 0.42560 0.57440 41 1 1 0.00000 1.00000 0.00000 42 0 0 0.86237 0.13763 0.86237 43 0 0 0.54800 0.45200 0.54800 44 1 1 0.00008 0.99992 0.00008 45 1 1 0.00000 1.00000 0.00000 46 0 0 0.70683 0.29317 0.70683 47 1 0 0.60319 0.39681 0.60319 48 1 1 0.00000 1.00000 0.00000

18:24 Saturday, November 21, 2009 252 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

Obs coast predict phat Pcoast Pnoncoast

49 0 0 0.86255 0.13745 0.86255 50 0 0 0.99881 0.00119 0.99881 51 0 0 0.55272 0.44728 0.55272 52 0 1 0.33103 0.66897 0.33103 53 0 0 0.71466 0.28534 0.71466 54 1 1 0.00150 0.99850 0.00150 55 1 1 0.00000 1.00000 0.00000 56 1 1 0.00292 0.99708 0.00292 57 1 1 0.00003 0.99997 0.00003 58 1 1 0.00000 1.00000 0.00000 59 1 1 0.00000 1.00000 0.00000 60 1 1 0.36846 0.63154 0.36846 61 0 0 0.97295 0.02705 0.97295 62 1 1 0.00079 0.99921 0.00079 63 1 1 0.00000 1.00000 0.00000 64 1 0 0.59615 0.40385 0.59615 65 1 1 0.00000 1.00000 0.00000 66 1 1 0.00079 0.99921 0.00079 67 0 0 0.92914 0.07086 0.92914 68 0 0 0.56271 0.43729 0.56271 69 0 0 0.99752 0.00248 0.99752 70 1 1 0.03945 0.96055 0.03945

18:24 Saturday, November 21, 2009 253 Classification Analysis on Coast using Monthly Average Temperature RULE: K Nearest Neighbor

Page 145: R Code for Calculating Beale’s F-Type Statistic: c1

The FREQ Procedure

Table of coast by predict

coast predict

Frequency‚ Percent ‚ Row Pct ‚ Col Pct ‚ 0‚ 1‚ Total ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 0 ‚ 30 ‚ 2 ‚ 32 ‚ 42.86 ‚ 2.86 ‚ 45.71 ‚ 93.75 ‚ 6.25 ‚ ‚ 85.71 ‚ 5.71 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 1 ‚ 5 ‚ 33 ‚ 38 ‚ 7.14 ‚ 47.14 ‚ 54.29 ‚ 13.16 ‚ 86.84 ‚ ‚ 14.29 ‚ 94.29 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ Total 35 35 70 50.00 50.00 100.00

18:24 Saturday, November 21, 2009 254 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 6 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

Pooled Covariance Matrix Information

Natural Log of the Covariance Determinant of the Matrix Rank Covariance Matrix

6 17.45328

18:24 Saturday, November 21, 2009 255 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure

Pairwise Generalized Squared Distances Between Groups

2 _ _ -1 _ _ D (i|j) = (X - X )' COV (X - X ) i j i j

Generalized Squared Distance to coast

Page 146: R Code for Calculating Beale’s F-Type Statistic: c1

From coast 0 1

0 0 2.09628 1 2.09628 0

Linear Discriminant Function

_ -1 _ -1 _ Constant = -.5 X' COV X Coefficient Vector = COV X j j j

Linear Discriminant Function for coast

Variable 0 1

Constant -2.37753 -1.77270 O3April -0.35218 -0.01620 O3May 0.77901 0.50974 O3June -0.13278 -0.00974 O3July 0.07060 -0.01823 O3Aug 0.05247 0.03917 O3Sep -0.21014 -0.03019

18:24 Saturday, November 21, 2009 256 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.8569 0.1431 2 1 0 * 0.9798 0.0202 3 1 0 * 0.8201 0.1799 4 1 1 0.0061 0.9939 5 1 1 0.1367 0.8633 6 1 0 * 0.6567 0.3433 7 1 1 0.1564 0.8436 8 1 0 * 0.6687 0.3313 9 1 0 * 0.7646 0.2354 10 0 0 0.5679 0.4321 11 0 0 0.8924 0.1076 12 0 0 0.9050 0.0950 13 0 1 * 0.3235 0.6765 14 1 1 0.4544 0.5456 15 0 0 0.8899 0.1101 16 1 1 0.0363 0.9637 17 1 1 0.1367 0.8633 18 0 0 0.8537 0.1463

Page 147: R Code for Calculating Beale’s F-Type Statistic: c1

19 0 0 0.6581 0.3419 20 1 1 0.1374 0.8626 21 0 0 0.9279 0.0721 22 0 0 0.9068 0.0932 23 1 1 0.2459 0.7541 24 0 0 0.9424 0.0576 25 1 1 0.0733 0.9267 26 1 1 0.1694 0.8306 27 0 0 0.9120 0.0880 28 1 1 0.4762 0.5238

18:24 Saturday, November 21, 2009 257 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.5994 0.4006 30 0 0 0.9159 0.0841 31 0 0 0.6802 0.3198 32 0 0 0.9091 0.0909 33 1 1 0.1329 0.8671 34 0 1 * 0.4943 0.5057 35 1 1 0.2213 0.7787 36 1 1 0.0430 0.9570 37 0 1 * 0.3521 0.6479 38 0 0 0.9197 0.0803 39 0 1 * 0.4736 0.5264 40 0 1 * 0.4773 0.5227 41 1 1 0.3728 0.6272 42 0 0 0.7814 0.2186 43 0 0 0.7089 0.2911 44 1 1 0.3200 0.6800 45 1 1 0.1857 0.8143 46 0 1 * 0.1437 0.8563 47 1 0 * 0.7164 0.2836 48 1 1 0.1674 0.8326 49 0 1 * 0.4657 0.5343 50 0 1 * 0.2849 0.7151 51 0 0 0.5958 0.4042 52 0 1 * 0.4946 0.5054 53 0 0 0.7980 0.2020 54 1 1 0.4735 0.5265 55 1 1 0.1050 0.8950 56 1 1 0.0226 0.9774 57 1 0 * 0.6223 0.3777 58 1 1 0.2609 0.7391 59 1 1 0.1841 0.8159 60 1 1 0.2003 0.7997 61 0 0 0.8425 0.1575 62 1 1 0.1317 0.8683 63 1 1 0.1447 0.8553 64 1 0 * 0.5737 0.4263 65 1 1 0.2279 0.7721 66 1 1 0.1189 0.8811 67 0 0 0.7597 0.2403 68 0 0 0.8260 0.1740 69 0 0 0.7050 0.2950

18:24 Saturday, November 21, 2009 258 Classification Analysis on Coast using

Page 148: R Code for Calculating Beale’s F-Type Statistic: c1

Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 1 0.2036 0.7964

* Misclassified observation

18:24 Saturday, November 21, 2009 259 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 23 9 32 71.88 28.13 100.00

1 9 29 38 23.68 76.32 100.00

Total 32 38 70 45.71 54.29 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.2813 0.2368 0.2590 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 260 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Page 149: R Code for Calculating Beale’s F-Type Statistic: c1

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.8486 0.1514 2 1 0 * 0.9944 0.0056 3 1 0 * 0.8895 0.1105 4 1 1 0.0033 0.9967 5 1 1 0.1812 0.8188 6 1 0 * 0.7892 0.2108 7 1 1 0.1830 0.8170 8 1 0 * 0.7206 0.2794 9 1 0 * 0.8786 0.1214 10 0 0 0.5516 0.4484 11 0 0 0.8882 0.1118 12 0 0 0.9005 0.0995 13 0 1 * 0.2755 0.7245 14 1 0 * 0.5166 0.4834 15 0 0 0.8702 0.1298 16 1 1 0.0346 0.9654 17 1 1 0.1549 0.8451 18 0 0 0.8465 0.1535 19 0 0 0.6197 0.3803 20 1 1 0.1456 0.8544 21 0 0 0.9228 0.0772 22 0 0 0.8996 0.1004 23 1 1 0.3298 0.6702 24 0 0 0.9395 0.0605 25 1 1 0.0757 0.9243 26 1 1 0.1837 0.8163 27 0 0 0.9049 0.0951 28 1 0 * 0.5314 0.4686

18:24 Saturday, November 21, 2009 261 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.7238 0.2762 30 0 0 0.9107 0.0893 31 0 0 0.6543 0.3457 32 0 0 0.9037 0.0963 33 1 1 0.1445 0.8555 34 0 1 * 0.4643 0.5357 35 1 1 0.2345 0.7655

Page 150: R Code for Calculating Beale’s F-Type Statistic: c1

36 1 1 0.0427 0.9573 37 0 1 * 0.1692 0.8308 38 0 0 0.9147 0.0853 39 0 1 * 0.4398 0.5602 40 0 1 * 0.4216 0.5784 41 1 1 0.3915 0.6085 42 0 0 0.7745 0.2255 43 0 0 0.6757 0.3243 44 1 1 0.4349 0.5651 45 1 1 0.2048 0.7952 46 0 1 * 0.0927 0.9073 47 1 0 * 0.8181 0.1819 48 1 1 0.1792 0.8208 49 0 1 * 0.3600 0.6400 50 0 1 * 0.1556 0.8444 51 0 0 0.5189 0.4811 52 0 1 * 0.4466 0.5534 53 0 0 0.7871 0.2129 54 1 0 * 0.5672 0.4328 55 1 1 0.1107 0.8893 56 1 1 0.0207 0.9793 57 1 0 * 0.7227 0.2773 58 1 1 0.2895 0.7105 59 1 1 0.2033 0.7967 60 1 1 0.2162 0.7838 61 0 0 0.8307 0.1693 62 1 1 0.1453 0.8547 63 1 1 0.1520 0.8480 64 1 0 * 0.6197 0.3803 65 1 1 0.2457 0.7543 66 1 1 0.1291 0.8709 67 0 0 0.7073 0.2927 68 0 0 0.7981 0.2019 69 0 0 0.6088 0.3912

18:24 Saturday, November 21, 2009 262 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 1 0.2569 0.7431

* Misclassified observation

18:24 Saturday, November 21, 2009 263 Classification Analysis on Coast using Monthly Average Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

Page 151: R Code for Calculating Beale’s F-Type Statistic: c1

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 23 9 32 71.88 28.13 100.00

1 12 26 38 31.58 68.42 100.00

Total 35 35 70 50.00 50.00 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.2813 0.3158 0.2985 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 264 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 6 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

18:24 Saturday, November 21, 2009 265 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR )

Page 152: R Code for Calculating Beale’s F-Type Statistic: c1

j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 0 * 0.8261 0.1739 3 1 0 * 0.6404 0.3596 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 1 0.4419 0.5581 7 1 1 0.0000 1.0000 8 1 1 0.4419 0.5581 9 1 1 0.4419 0.5581 10 0 0 0.6404 0.3596 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 1 * 0.4419 0.5581 14 1 1 0.4419 0.5581 15 0 0 0.8261 0.1739 16 1 1 0.0000 1.0000 17 1 1 0.2289 0.7711 18 0 0 1.0000 0.0000 19 0 0 1.0000 0.0000 20 1 0 * 0.6404 0.3596 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 1.0000 0.0000 25 1 1 0.0000 1.0000 26 1 1 0.4419 0.5581 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 266 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 0 * 0.6404 0.3596 29 1 0 * 0.6404 0.3596 30 0 0 1.0000 0.0000 31 0 0 1.0000 0.0000 32 0 0 1.0000 0.0000 33 1 1 0.2289 0.7711 34 0 0 0.6404 0.3596 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 1 * 0.2289 0.7711 38 0 0 0.8261 0.1739 39 0 1 * 0.4419 0.5581 40 0 0 0.6404 0.3596 41 1 1 0.4419 0.5581 42 0 0 1.0000 0.0000 43 0 0 0.6404 0.3596 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 1 * 0.2289 0.7711

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47 1 0 * 0.6404 0.3596 48 1 1 0.0000 1.0000 49 0 0 1.0000 0.0000 50 0 1 * 0.4419 0.5581 51 0 0 0.8261 0.1739 52 0 0 0.6404 0.3596 53 0 0 0.8261 0.1739 54 1 1 0.2289 0.7711 55 1 1 0.2289 0.7711 56 1 1 0.0000 1.0000 57 1 1 0.2289 0.7711 58 1 1 0.0000 1.0000 59 1 1 0.2289 0.7711 60 1 1 0.4419 0.5581 61 0 0 1.0000 0.0000 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 0 * 0.6404 0.3596 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 1.0000 0.0000 68 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 267 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 1.0000 0.0000 70 1 1 0.2289 0.7711

* Misclassified observation

18:24 Saturday, November 21, 2009 268 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

Page 154: R Code for Calculating Beale’s F-Type Statistic: c1

0 27 5 32 84.38 15.63 100.00

1 7 31 38 18.42 81.58 100.00

Total 34 36 70 48.57 51.43 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1563 0.1842 0.1702 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 269 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 0 * 1.0000 0.0000 3 1 0 * 0.8222 0.1778 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 0 * 0.6343 0.3657 7 1 1 0.2242 0.7758 8 1 0 * 0.6343 0.3657 9 1 0 * 0.6343 0.3657 10 0 0 0.6477 0.3523 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 1 * 0.2346 0.7654 14 1 0 * 0.6343 0.3657 15 0 0 0.8306 0.1694 16 1 1 0.0000 1.0000 17 1 1 0.4353 0.5647 18 0 0 1.0000 0.0000 19 0 0 1.0000 0.0000 20 1 0 * 0.6343 0.3657 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000

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23 1 1 0.0000 1.0000 24 0 0 1.0000 0.0000 25 1 1 0.0000 1.0000 26 1 1 0.4353 0.5647 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 270 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 0 * 0.8222 0.1778 29 1 0 * 0.6343 0.3657 30 0 0 1.0000 0.0000 31 0 0 1.0000 0.0000 32 0 0 0.8306 0.1694 33 1 1 0.2242 0.7758 34 0 0 0.6477 0.3523 35 1 1 0.2242 0.7758 36 1 1 0.0000 1.0000 37 0 1 * 0.2346 0.7654 38 0 0 0.8306 0.1694 39 0 1 * 0.4497 0.5503 40 0 1 * 0.4497 0.5503 41 1 1 0.4353 0.5647 42 0 0 1.0000 0.0000 43 0 0 0.6477 0.3523 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 1 * 0.2346 0.7654 47 1 0 * 0.8222 0.1778 48 1 1 0.2242 0.7758 49 0 0 1.0000 0.0000 50 0 1 * 0.4497 0.5503 51 0 0 0.8306 0.1694 52 0 0 0.6477 0.3523 53 0 0 0.8306 0.1694 54 1 1 0.4353 0.5647 55 1 1 0.2242 0.7758 56 1 1 0.0000 1.0000 57 1 1 0.4353 0.5647 58 1 1 0.2242 0.7758 59 1 1 0.4353 0.5647 60 1 0 * 0.6343 0.3657 61 0 0 0.8306 0.1694 62 1 1 0.2242 0.7758 63 1 1 0.2242 0.7758 64 1 0 * 0.8222 0.1778 65 1 1 0.2242 0.7758 66 1 1 0.2242 0.7758 67 0 0 1.0000 0.0000 68 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 271 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB

Page 156: R Code for Calculating Beale’s F-Type Statistic: c1

Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 1.0000 0.0000 70 1 1 0.2242 0.7758

* Misclassified observation

18:24 Saturday, November 21, 2009 272 Classification Analysis on Coast using Monthly Average Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 26 6 32 81.25 18.75 100.00

1 12 26 38 31.58 68.42 100.00

Total 38 32 70 54.29 45.71 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1875 0.3158 0.2516 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 273 Classification Analysis on Coast using Monthly Average Ozone Logistic Regression

The LOGISTIC Procedure

Model Information

Data Set WORK.PCCOMB Response Variable coast

Page 157: R Code for Calculating Beale’s F-Type Statistic: c1

Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring

Number of Observations Read 70 Number of Observations Used 70

Response Profile

Ordered Total Value coast Frequency

1 0 32 2 1 38

Probability modeled is coast=0.

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

Model Fit Statistics

Intercept Intercept and Criterion Only Covariates

AIC 98.526 80.645 SC 100.774 96.385 -2 Log L 96.526 66.645

Testing Global Null Hypothesis: BETA=0

Test Chi-Square DF Pr > ChiSq

Likelihood Ratio 29.8806 6 <.0001 Score 24.4129 6 0.0004 Wald 17.6277 6 0.0072

18:24 Saturday, November 21, 2009 274 Classification Analysis on Coast using Monthly Average Ozone Logistic Regression

The LOGISTIC Procedure

Analysis of Maximum Likelihood Estimates

Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq

Intercept 1 -1.1161 0.7210 2.3960 0.1216 O3April 1 -0.3345 0.1081 9.5860 0.0020 O3May 1 0.3177 0.1442 4.8522 0.0276 O3June 1 -0.1386 0.1024 1.8335 0.1757 O3July 1 0.1069 0.0758 1.9918 0.1582 O3Aug 1 0.00472 0.0570 0.0068 0.9341 O3Sep 1 -0.1952 0.0857 5.1891 0.0227

Odds Ratio Estimates

Point 95% Wald Effect Estimate Confidence Limits

Page 158: R Code for Calculating Beale’s F-Type Statistic: c1

O3April 0.716 0.579 0.884 O3May 1.374 1.036 1.823 O3June 0.871 0.712 1.064 O3July 1.113 0.959 1.291 O3Aug 1.005 0.898 1.124 O3Sep 0.823 0.696 0.973

Association of Predicted Probabilities and Observed Responses

Percent Concordant 86.2 Somers' D 0.724 Percent Discordant 13.8 Gamma 0.724 Percent Tied 0.0 Tau-a 0.364 Pairs 1216 c 0.862

18:24 Saturday, November 21, 2009 275 Classification Analysis on Coast using Monthly Average Ozone Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

1 0 0 0.82524 0.17476 0.82524 2 1 0 0.97565 0.02435 0.97565 3 1 0 0.73438 0.26562 0.73438 4 1 1 0.00282 0.99718 0.00282 5 1 1 0.10372 0.89628 0.10372 6 1 0 0.64631 0.35369 0.64631 7 1 1 0.11823 0.88177 0.11823 8 1 0 0.66766 0.33234 0.66766 9 1 0 0.68933 0.31067 0.68933 10 0 0 0.51712 0.48288 0.51712 11 0 0 0.86406 0.13594 0.86406 12 0 0 0.87987 0.12013 0.87987 13 0 1 0.31772 0.68228 0.31772 14 1 1 0.31366 0.68634 0.31366 15 0 0 0.86081 0.13919 0.86081 16 1 1 0.02246 0.97754 0.02246 17 1 1 0.08207 0.91793 0.08207 18 0 0 0.81206 0.18794 0.81206 19 0 0 0.68644 0.31356 0.68644 20 1 1 0.12310 0.87690 0.12310 21 0 0 0.88938 0.11062 0.88938 22 0 0 0.88217 0.11783 0.88217 23 1 1 0.22764 0.77236 0.22764 24 0 0 0.93542 0.06458 0.93542 25 1 1 0.04870 0.95130 0.04870 26 1 1 0.12154 0.87846 0.12154 27 0 0 0.88221 0.11779 0.88221 28 1 1 0.34917 0.65083 0.34917 29 1 0 0.57474 0.42526 0.57474 30 0 0 0.91952 0.08048 0.91952 31 0 0 0.68131 0.31869 0.68131 32 0 0 0.89751 0.10249 0.89751 33 1 1 0.11388 0.88612 0.11388 34 0 1 0.40092 0.59908 0.40092 35 1 1 0.18093 0.81907 0.18093 36 1 1 0.02488 0.97512 0.02488 37 0 1 0.37069 0.62931 0.37069 38 0 0 0.88554 0.11446 0.88554 39 0 1 0.41636 0.58364 0.41636 40 0 1 0.39374 0.60626 0.39374 41 1 1 0.35078 0.64922 0.35078 42 0 0 0.71599 0.28401 0.71599 43 0 0 0.59784 0.40216 0.59784 44 1 1 0.29713 0.70287 0.29713 45 1 1 0.17650 0.82350 0.17650 46 0 1 0.10968 0.89032 0.10968

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47 1 0 0.64541 0.35459 0.64541 48 1 1 0.15801 0.84199 0.15801

18:24 Saturday, November 21, 2009 276 Classification Analysis on Coast using Monthly Average Ozone Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

49 0 1 0.42767 0.57233 0.42767 50 0 1 0.19994 0.80006 0.19994 51 0 0 0.61468 0.38532 0.61468 52 0 0 0.50133 0.49867 0.50133 53 0 0 0.77225 0.22775 0.77225 54 1 1 0.46826 0.53174 0.46826 55 1 1 0.08558 0.91442 0.08558 56 1 1 0.01330 0.98670 0.01330 57 1 0 0.60732 0.39268 0.60732 58 1 1 0.25702 0.74298 0.25702 59 1 1 0.18330 0.81670 0.18330 60 1 1 0.14217 0.85783 0.14217 61 0 0 0.81492 0.18508 0.81492 62 1 1 0.11686 0.88314 0.11686 63 1 1 0.12658 0.87342 0.12658 64 1 0 0.53519 0.46481 0.53519 65 1 1 0.20042 0.79958 0.20042 66 1 1 0.10590 0.89410 0.10590 67 0 0 0.64869 0.35131 0.64869 68 0 0 0.82488 0.17512 0.82488 69 0 0 0.69748 0.30252 0.69748 70 1 1 0.16601 0.83399 0.16601

18:24 Saturday, November 21, 2009 277 Classification Analysis on Coast using Monthly Average Ozone Logistic Regression

The FREQ Procedure

Table of coast by predict

coast predict

Frequency‚ Percent ‚ Row Pct ‚ Col Pct ‚ 0‚ 1‚ Total ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 0 ‚ 24 ‚ 8 ‚ 32 ‚ 34.29 ‚ 11.43 ‚ 45.71 ‚ 75.00 ‚ 25.00 ‚ ‚ 72.73 ‚ 21.62 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 1 ‚ 9 ‚ 29 ‚ 38 ‚ 12.86 ‚ 41.43 ‚ 54.29 ‚ 23.68 ‚ 76.32 ‚ ‚ 27.27 ‚ 78.38 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ Total 33 37 70 47.14 52.86 100.00

18:24 Saturday, November 21, 2009 278 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure

Page 160: R Code for Calculating Beale’s F-Type Statistic: c1

Observations 70 DF Total 69 Variables 12 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

Pooled Covariance Matrix Information

Natural Log of the Covariance Determinant of the Matrix Rank Covariance Matrix

12 23.26300

18:24 Saturday, November 21, 2009 279 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure

Pairwise Generalized Squared Distances Between Groups

2 _ _ -1 _ _ D (i|j) = (X - X )' COV (X - X ) i j i j

Generalized Squared Distance to coast

From coast 0 1

0 0 7.56965 1 7.56965 0

Linear Discriminant Function

_ -1 _ -1 _ Constant = -.5 X' COV X Coefficient Vector = COV X j j j

Linear Discriminant Function for coast

Variable 0 1

Constant -240.98213 -242.86285 TempApril 6.16044 6.71952 TempMay -11.92825 -11.77997 TempJune -2.68980 -3.69295 TempJuly 6.02534 4.94120 TempAug 7.09561 8.63237 TempSep 1.25255 1.30838 O3April -0.97394 -0.68315 O3May 0.81989 -0.12855 O3June 1.84824 2.47401 O3July 2.05744 2.38877 O3Aug -4.93361 -5.41257 O3Sep -0.20421 -0.04591

18:24 Saturday, November 21, 2009 280

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Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.9342 0.0658 2 1 1 0.4855 0.5145 3 1 1 0.0789 0.9211 4 1 1 0.0003 0.9997 5 1 1 0.0032 0.9968 6 1 0 * 0.6539 0.3461 7 1 0 * 0.7789 0.2211 8 1 0 * 0.9654 0.0346 9 1 1 0.0261 0.9739 10 0 0 0.9990 0.0010 11 0 0 0.9947 0.0053 12 0 0 0.9879 0.0121 13 0 0 0.9701 0.0299 14 1 1 0.0228 0.9772 15 0 0 0.9777 0.0223 16 1 1 0.0029 0.9971 17 1 1 0.0276 0.9724 18 0 0 0.9729 0.0271 19 0 0 0.9946 0.0054 20 1 1 0.0364 0.9636 21 0 0 0.9942 0.0058 22 0 0 0.9966 0.0034 23 1 1 0.0363 0.9637 24 0 0 0.9735 0.0265 25 1 1 0.0133 0.9867 26 1 1 0.2176 0.7824 27 0 0 0.9948 0.0052 28 1 1 0.2922 0.7078

18:24 Saturday, November 21, 2009 281 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

Page 162: R Code for Calculating Beale’s F-Type Statistic: c1

29 1 1 0.0793 0.9207 30 0 0 0.9998 0.0002 31 0 0 0.9940 0.0060 32 0 0 0.9973 0.0027 33 1 0 * 0.5106 0.4894 34 0 0 0.6512 0.3488 35 1 1 0.0193 0.9807 36 1 1 0.0060 0.9940 37 0 0 0.8500 0.1500 38 0 0 0.9935 0.0065 39 0 0 0.9960 0.0040 40 0 0 0.9831 0.0169 41 1 1 0.0059 0.9941 42 0 0 0.9871 0.0129 43 0 0 0.9475 0.0525 44 1 1 0.0406 0.9594 45 1 1 0.0004 0.9996 46 0 1 * 0.3738 0.6262 47 1 1 0.0812 0.9188 48 1 1 0.0001 0.9999 49 0 0 0.8877 0.1123 50 0 0 0.9877 0.0123 51 0 0 0.7094 0.2906 52 0 1 * 0.2368 0.7632 53 0 0 0.7593 0.2407 54 1 1 0.0198 0.9802 55 1 1 0.0005 0.9995 56 1 1 0.0004 0.9996 57 1 1 0.0512 0.9488 58 1 1 0.0002 0.9998 59 1 1 0.0376 0.9624 60 1 1 0.0095 0.9905 61 0 0 0.9973 0.0027 62 1 1 0.0016 0.9984 63 1 1 0.0017 0.9983 64 1 0 * 0.9304 0.0696 65 1 1 0.0008 0.9992 66 1 1 0.0028 0.9972 67 0 0 0.5892 0.4108 68 0 0 0.8608 0.1392 69 0 0 0.9994 0.0006

18:24 Saturday, November 21, 2009 282 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 1 0.1097 0.8903

* Misclassified observation

18:24 Saturday, November 21, 2009 283 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using Linear Discriminant Function

Page 163: R Code for Calculating Beale’s F-Type Statistic: c1

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 30 2 32 93.75 6.25 100.00

1 5 33 38 13.16 86.84 100.00

Total 35 35 70 50.00 50.00 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.0625 0.1316 0.0970 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 284 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.9141 0.0859 2 1 0 * 0.9042 0.0958 3 1 1 0.1446 0.8554 4 1 1 0.0001 0.9999 5 1 1 0.0032 0.9968 6 1 0 * 0.9591 0.0409

Page 164: R Code for Calculating Beale’s F-Type Statistic: c1

7 1 0 * 0.9902 0.0098 8 1 0 * 0.9930 0.0070 9 1 1 0.0465 0.9535 10 0 0 0.9990 0.0010 11 0 0 0.9942 0.0058 12 0 0 0.9862 0.0138 13 0 0 0.9443 0.0557 14 1 1 0.0326 0.9674 15 0 0 0.9653 0.0347 16 1 1 0.0029 0.9971 17 1 1 0.0390 0.9610 18 0 0 0.9689 0.0311 19 0 0 0.9933 0.0067 20 1 1 0.0930 0.9070 21 0 0 0.9932 0.0068 22 0 0 0.9963 0.0037 23 1 1 0.0704 0.9296 24 0 0 0.9607 0.0393 25 1 1 0.0162 0.9838 26 1 1 0.3490 0.6510 27 0 0 0.9940 0.0060 28 1 1 0.4178 0.5822

18:24 Saturday, November 21, 2009 285 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 1 0.1830 0.8170 30 0 0 0.9999 0.0001 31 0 0 0.9929 0.0071 32 0 0 0.9972 0.0028 33 1 0 * 0.8983 0.1017 34 0 0 0.5480 0.4520 35 1 1 0.0237 0.9763 36 1 1 0.0066 0.9934 37 0 1 * 0.3705 0.6295 38 0 0 0.9924 0.0076 39 0 0 0.9953 0.0047 40 0 0 0.9770 0.0230 41 1 1 0.0071 0.9929 42 0 0 0.9847 0.0153 43 0 0 0.9182 0.0818 44 1 1 0.1357 0.8643 45 1 1 0.0003 0.9997 46 0 1 * 0.0762 0.9238 47 1 1 0.1566 0.8434 48 1 1 0.0001 0.9999 49 0 0 0.8094 0.1906 50 0 0 0.9789 0.0211 51 0 0 0.5438 0.4562 52 0 1 * 0.0024 0.9976 53 0 0 0.6537 0.3463 54 1 1 0.0373 0.9627 55 1 1 0.0004 0.9996 56 1 1 0.0003 0.9997 57 1 1 0.0968 0.9032 58 1 1 0.0001 0.9999 59 1 1 0.0903 0.9097 60 1 1 0.0116 0.9884

Page 165: R Code for Calculating Beale’s F-Type Statistic: c1

61 0 0 0.9971 0.0029 62 1 1 0.0014 0.9986 63 1 1 0.0017 0.9983 64 1 0 * 0.9843 0.0157 65 1 1 0.0005 0.9995 66 1 1 0.0027 0.9973 67 0 1 * 0.2550 0.7450 68 0 0 0.7718 0.2282 69 0 0 0.9996 0.0004

18:24 Saturday, November 21, 2009 286 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 1 0.2269 0.7731

* Misclassified observation

18:24 Saturday, November 21, 2009 287 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 28 4 32 87.50 12.50 100.00

1 6 32 38 15.79 84.21 100.00

Total 34 36 70 48.57 51.43 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Page 166: R Code for Calculating Beale’s F-Type Statistic: c1

Rate 0.1250 0.1579 0.1414 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 288 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 12 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

18:24 Saturday, November 21, 2009 289 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 1 0.2289 0.7711 3 1 1 0.2289 0.7711 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 1 0.2289 0.7711 7 1 0 * 0.6404 0.3596 8 1 0 * 0.6404 0.3596 9 1 1 0.2289 0.7711 10 0 0 0.8261 0.1739 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 0 1.0000 0.0000 14 1 1 0.0000 1.0000 15 0 0 1.0000 0.0000 16 1 1 0.0000 1.0000 17 1 1 0.2289 0.7711

Page 167: R Code for Calculating Beale’s F-Type Statistic: c1

18 0 0 1.0000 0.0000 19 0 0 1.0000 0.0000 20 1 1 0.0000 1.0000 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 1.0000 0.0000 25 1 1 0.0000 1.0000 26 1 0 * 0.6404 0.3596 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 290 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 0 * 0.6404 0.3596 29 1 1 0.4419 0.5581 30 0 0 1.0000 0.0000 31 0 0 1.0000 0.0000 32 0 0 1.0000 0.0000 33 1 0 * 0.8261 0.1739 34 0 0 0.8261 0.1739 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 0 0.8261 0.1739 38 0 0 1.0000 0.0000 39 0 0 1.0000 0.0000 40 0 0 0.8261 0.1739 41 1 1 0.0000 1.0000 42 0 0 1.0000 0.0000 43 0 0 0.8261 0.1739 44 1 1 0.2289 0.7711 45 1 1 0.0000 1.0000 46 0 0 0.6404 0.3596 47 1 1 0.4419 0.5581 48 1 1 0.0000 1.0000 49 0 0 1.0000 0.0000 50 0 0 1.0000 0.0000 51 0 0 0.6404 0.3596 52 0 0 0.6404 0.3596 53 0 0 1.0000 0.0000 54 1 1 0.2289 0.7711 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.0000 1.0000 58 1 1 0.0000 1.0000 59 1 1 0.2289 0.7711 60 1 1 0.2289 0.7711 61 0 0 1.0000 0.0000 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 0 * 0.6404 0.3596 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 0.8261 0.1739 68 0 0 0.8261 0.1739

18:24 Saturday, November 21, 2009 291 Classification Analysis on Coast using

Page 168: R Code for Calculating Beale’s F-Type Statistic: c1

Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 1.0000 0.0000 70 1 0 * 0.6404 0.3596

* Misclassified observation

18:24 Saturday, November 21, 2009 292 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 32 0 32 100.00 0.00 100.00

1 7 31 38 18.42 81.58 100.00

Total 39 31 70 55.71 44.29 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.0000 0.1842 0.0921 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 293 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure

Page 169: R Code for Calculating Beale’s F-Type Statistic: c1

Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 1 0.2242 0.7758 3 1 1 0.2242 0.7758 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 1 0.4353 0.5647 7 1 0 * 0.8222 0.1778 8 1 0 * 0.8222 0.1778 9 1 1 0.2242 0.7758 10 0 0 0.6477 0.3523 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 0 1.0000 0.0000 14 1 1 0.0000 1.0000 15 0 0 1.0000 0.0000 16 1 1 0.0000 1.0000 17 1 1 0.2242 0.7758 18 0 0 1.0000 0.0000 19 0 0 1.0000 0.0000 20 1 1 0.0000 1.0000 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 1.0000 0.0000 25 1 1 0.0000 1.0000 26 1 0 * 0.8222 0.1778 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 294 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 0 * 0.6343 0.3657 29 1 0 * 0.6343 0.3657 30 0 0 0.8306 0.1694 31 0 0 1.0000 0.0000 32 0 0 1.0000 0.0000

Page 170: R Code for Calculating Beale’s F-Type Statistic: c1

33 1 0 * 1.0000 0.0000 34 0 0 0.6477 0.3523 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 0 0.6477 0.3523 38 0 0 1.0000 0.0000 39 0 0 1.0000 0.0000 40 0 0 0.8306 0.1694 41 1 1 0.0000 1.0000 42 0 0 1.0000 0.0000 43 0 0 0.8306 0.1694 44 1 1 0.2242 0.7758 45 1 1 0.0000 1.0000 46 0 0 0.6477 0.3523 47 1 1 0.4353 0.5647 48 1 1 0.0000 1.0000 49 0 0 1.0000 0.0000 50 0 0 1.0000 0.0000 51 0 0 0.6477 0.3523 52 0 1 * 0.4497 0.5503 53 0 0 0.8306 0.1694 54 1 1 0.2242 0.7758 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.2242 0.7758 58 1 1 0.0000 1.0000 59 1 1 0.4353 0.5647 60 1 1 0.2242 0.7758 61 0 0 1.0000 0.0000 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 0 * 0.8222 0.1778 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 0.8306 0.1694 68 0 0 0.8306 0.1694

18:24 Saturday, November 21, 2009 295 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 1.0000 0.0000 70 1 0 * 0.8222 0.1778

* Misclassified observation

18:24 Saturday, November 21, 2009 296 Classification Analysis on Coast using Monthly Average Temperature and Ozone RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Page 171: R Code for Calculating Beale’s F-Type Statistic: c1

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 31 1 32 96.88 3.13 100.00

1 8 30 38 21.05 78.95 100.00

Total 39 31 70 55.71 44.29 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.0313 0.2105 0.1209 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 297 Classification Analysis on Coast using Monthly Average Temperature and Ozone Logistic Regression

The LOGISTIC Procedure

Model Information

Data Set WORK.PCCOMB Response Variable coast Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring

Number of Observations Read 70 Number of Observations Used 70

Response Profile

Ordered Total Value coast Frequency

1 0 32 2 1 38

Probability modeled is coast=0.

Model Convergence Status

Complete separation of data points detected.

WARNING: The maximum likelihood estimate does not exist.

Page 172: R Code for Calculating Beale’s F-Type Statistic: c1

WARNING: The LOGISTIC procedure continues in spite of the above warning. Results shown are based on the last maximum likelihood iteration. Validity of the model fit is questionable.

Model Fit Statistics

Intercept Intercept and Criterion Only Covariates

AIC 98.526 29.540 SC 100.774 58.770 -2 Log L 96.526 3.540

18:24 Saturday, November 21, 2009 298 Classification Analysis on Coast using Monthly Average Temperature and Ozone Logistic Regression

The LOGISTIC ProcedureWARNING: The validity of the model fit is questionable.

Testing Global Null Hypothesis: BETA=0

Test Chi-Square DF Pr > ChiSq

Likelihood Ratio 92.9857 12 <.0001 Score 46.1398 12 <.0001 Wald 3.4545 12 0.9914

Analysis of Maximum Likelihood Estimates

Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq

Intercept 1 -208.0 199.1 1.0920 0.2960 TempApril 1 -4.6674 5.0114 0.8674 0.3517 TempMay 1 4.2296 9.6882 0.1906 0.6624 TempJune 1 7.7365 13.7107 0.3184 0.5726 TempJuly 1 16.2033 16.0705 1.0166 0.3133 TempAug 1 -17.6889 19.7679 0.8007 0.3709 TempSep 1 -4.8531 10.9343 0.1970 0.6572 O3April 1 0.6090 1.9657 0.0960 0.7567 O3May 1 6.0793 5.5518 1.1991 0.2735 O3June 1 -2.1634 9.4552 0.0524 0.8190 O3July 1 -5.4650 5.7307 0.9094 0.3403 O3Aug 1 7.4131 7.1973 1.0609 0.3030 O3Sep 1 -3.5295 6.2016 0.3239 0.5693

Odds Ratio Estimates

Point 95% Wald Effect Estimate Confidence Limits

TempApril 0.009 <0.001 173.256 TempMay 68.690 <0.001 >999.999 TempJune >999.999 <0.001 >999.999 TempJuly >999.999 <0.001 >999.999 TempAug <0.001 <0.001 >999.999 TempSep 0.008 <0.001 >999.999 O3April 1.839 0.039 86.638 O3May 436.721 0.008 >999.999 O3June 0.115 <0.001 >999.999 O3July 0.004 <0.001 319.593

Page 173: R Code for Calculating Beale’s F-Type Statistic: c1

O3Aug >999.999 0.001 >999.999 O3Sep 0.029 <0.001 >999.999

18:24 Saturday, November 21, 2009 299 Classification Analysis on Coast using Monthly Average Temperature and Ozone Logistic Regression

The LOGISTIC ProcedureWARNING: The validity of the model fit is questionable.

Association of Predicted Probabilities and Observed Responses

Percent Concordant 86.8 Somers' D 0.868 Percent Discordant 0.0 Gamma 1.000 Percent Tied 13.2 Tau-a 0.437 Pairs 1216 c 0.934

18:24 Saturday, November 21, 2009 300 Classification Analysis on Coast using Monthly Average Temperature and Ozone Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

1 0 0 1.00000 0.00000 1.00000 2 1 1 0.21050 0.78950 0.21050 3 1 1 0.00000 1.00000 0.00000 4 1 1 0.00000 1.00000 0.00000 5 1 1 0.00000 1.00000 0.00000 6 1 1 0.00619 0.99381 0.00619 7 1 1 0.09764 0.90236 0.09764 8 1 1 0.23667 0.76333 0.23667 9 1 1 0.00038 0.99962 0.00038 10 0 0 1.00000 0.00000 1.00000 11 0 0 1.00000 0.00000 1.00000 12 0 0 1.00000 0.00000 1.00000 13 0 0 0.83017 0.16983 0.83017 14 1 1 0.00000 1.00000 0.00000 15 0 0 1.00000 0.00000 1.00000 16 1 1 0.00000 1.00000 0.00000 17 1 1 0.00000 1.00000 0.00000 18 0 0 1.00000 0.00000 1.00000 19 0 0 1.00000 0.00000 1.00000 20 1 1 0.12059 0.87941 0.12059 21 0 0 1.00000 0.00000 1.00000 22 0 0 1.00000 0.00000 1.00000 23 1 1 0.00000 1.00000 0.00000 24 0 0 1.00000 0.00000 1.00000 25 1 1 0.00000 1.00000 0.00000 26 1 1 0.00033 0.99967 0.00033 27 0 0 1.00000 0.00000 1.00000 28 1 1 0.00255 0.99745 0.00255 29 1 1 0.00000 1.00000 0.00000 30 0 0 1.00000 0.00000 1.00000 31 0 0 1.00000 0.00000 1.00000 32 0 0 1.00000 0.00000 1.00000 33 1 1 0.09715 0.90285 0.09715 34 0 0 0.99881 0.00119 0.99881 35 1 1 0.00000 1.00000 0.00000 36 1 1 0.00000 1.00000 0.00000 37 0 0 1.00000 0.00000 1.00000 38 0 0 1.00000 0.00000 1.00000 39 0 0 1.00000 0.00000 1.00000 40 0 0 1.00000 0.00000 1.00000 41 1 1 0.00000 1.00000 0.00000 42 0 0 1.00000 0.00000 1.00000 43 0 0 1.00000 0.00000 1.00000 44 1 1 0.00000 1.00000 0.00000

Page 174: R Code for Calculating Beale’s F-Type Statistic: c1

45 1 1 0.00000 1.00000 0.00000 46 0 0 1.00000 0.00000 1.00000 47 1 1 0.00000 1.00000 0.00000 48 1 1 0.00000 1.00000 0.00000

18:24 Saturday, November 21, 2009 301 Classification Analysis on Coast using Monthly Average Temperature and Ozone Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

49 0 0 1.00000 0.00000 1.00000 50 0 0 0.99999 0.00001 0.99999 51 0 0 0.99996 0.00004 0.99996 52 0 0 0.80695 0.19305 0.80695 53 0 0 0.68272 0.31728 0.68272 54 1 1 0.00000 1.00000 0.00000 55 1 1 0.00000 1.00000 0.00000 56 1 1 0.00000 1.00000 0.00000 57 1 1 0.00000 1.00000 0.00000 58 1 1 0.00000 1.00000 0.00000 59 1 1 0.00000 1.00000 0.00000 60 1 1 0.00000 1.00000 0.00000 61 0 0 1.00000 0.00000 1.00000 62 1 1 0.00000 1.00000 0.00000 63 1 1 0.00000 1.00000 0.00000 64 1 1 0.00373 0.99627 0.00373 65 1 1 0.00000 1.00000 0.00000 66 1 1 0.00000 1.00000 0.00000 67 0 0 0.87513 0.12487 0.87513 68 0 0 0.99999 0.00001 0.99999 69 0 0 1.00000 0.00000 1.00000 70 1 1 0.00000 1.00000 0.00000

18:24 Saturday, November 21, 2009 302 Classification Analysis on Coast using Monthly Average Temperature and Ozone Logistic Regression

The FREQ Procedure

Table of coast by predict

coast predict

Frequency‚ Percent ‚ Row Pct ‚ Col Pct ‚ 0‚ 1‚ Total ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 0 ‚ 32 ‚ 0 ‚ 32 ‚ 45.71 ‚ 0.00 ‚ 45.71 ‚ 100.00 ‚ 0.00 ‚ ‚ 100.00 ‚ 0.00 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 1 ‚ 0 ‚ 38 ‚ 38 ‚ 0.00 ‚ 54.29 ‚ 54.29 ‚ 0.00 ‚ 100.00 ‚ ‚ 0.00 ‚ 100.00 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ Total 32 38 70 45.71 54.29 100.00

18:24 Saturday, November 21, 2009 303 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

Page 175: R Code for Calculating Beale’s F-Type Statistic: c1

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 2 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

Pooled Covariance Matrix Information

Natural Log of the Covariance Determinant of the Matrix Rank Covariance Matrix

2 8.10750

18:24 Saturday, November 21, 2009 304 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure

Pairwise Generalized Squared Distances Between Groups

2 _ _ -1 _ _ D (i|j) = (X - X )' COV (X - X ) i j i j

Generalized Squared Distance to coast

From coast 0 1

0 0 2.55616 1 2.55616 0

Linear Discriminant Function

_ -1 _ -1 _ Constant = -.5 X' COV X Coefficient Vector = COV X j j j

Linear Discriminant Function for coast

Variable 0 1

Constant -0.37664 -0.26709 PCT1 -0.03188 0.02685 PCT2 0.21061 -0.17735

18:24 Saturday, November 21, 2009 305 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Page 176: R Code for Calculating Beale’s F-Type Statistic: c1

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.7374 0.2626 2 1 0 * 0.8447 0.1553 3 1 1 0.1499 0.8501 4 1 1 0.0813 0.9187 5 1 1 0.4831 0.5169 6 1 1 0.0632 0.9368 7 1 0 * 0.8507 0.1493 8 1 0 * 0.8799 0.1201 9 1 1 0.3009 0.6991 10 0 0 0.9030 0.0970 11 0 0 0.7198 0.2802 12 0 0 0.7925 0.2075 13 0 0 0.9179 0.0821 14 1 1 0.1555 0.8445 15 0 0 0.7872 0.2128 16 1 1 0.0310 0.9690 17 1 1 0.4030 0.5970 18 0 0 0.7492 0.2508 19 0 0 0.9456 0.0544 20 1 1 0.3551 0.6449 21 0 0 0.5929 0.4071 22 0 0 0.8501 0.1499 23 1 0 * 0.5191 0.4809 24 0 0 0.8024 0.1976 25 1 1 0.0691 0.9309 26 1 1 0.1772 0.8228 27 0 0 0.7394 0.2606 28 1 1 0.1318 0.8682

18:24 Saturday, November 21, 2009 306 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.8841 0.1159 30 0 0 0.8796 0.1204 31 0 0 0.9126 0.0874 32 0 0 0.8425 0.1575 33 1 0 * 0.8772 0.1228 34 0 1 * 0.3387 0.6613 35 1 1 0.0465 0.9535 36 1 1 0.0659 0.9341

Page 177: R Code for Calculating Beale’s F-Type Statistic: c1

37 0 0 0.8942 0.1058 38 0 0 0.6715 0.3285 39 0 0 0.9284 0.0716 40 0 1 * 0.4177 0.5823 41 1 1 0.0524 0.9476 42 0 0 0.7166 0.2834 43 0 1 * 0.2885 0.7115 44 1 1 0.0118 0.9882 45 1 1 0.1644 0.8356 46 0 1 * 0.4465 0.5535 47 1 0 * 0.8772 0.1228 48 1 1 0.0135 0.9865 49 0 0 0.6128 0.3872 50 0 0 0.9149 0.0851 51 0 0 0.8701 0.1299 52 0 0 0.8279 0.1721 53 0 0 0.6967 0.3033 54 1 0 * 0.5536 0.4464 55 1 1 0.1428 0.8572 56 1 1 0.0853 0.9147 57 1 1 0.2087 0.7913 58 1 1 0.0135 0.9865 59 1 1 0.0524 0.9476 60 1 1 0.1705 0.8295 61 0 0 0.7251 0.2749 62 1 1 0.0321 0.9679 63 1 1 0.1684 0.8316 64 1 0 * 0.8865 0.1135 65 1 1 0.0951 0.9049 66 1 1 0.0321 0.9679 67 0 0 0.8208 0.1792 68 0 0 0.7964 0.2036 69 0 0 0.8696 0.1304

18:24 Saturday, November 21, 2009 307 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 0 * 0.8099 0.1901

* Misclassified observation

18:24 Saturday, November 21, 2009 308 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

Page 178: R Code for Calculating Beale’s F-Type Statistic: c1

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 28 4 32 87.50 12.50 100.00

1 10 28 38 26.32 73.68 100.00

Total 38 32 70 54.29 45.71 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1250 0.2632 0.1941 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 309 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.7298 0.2702 2 1 0 * 0.8679 0.1321 3 1 1 0.1533 0.8467 4 1 1 0.0847 0.9153 5 1 1 0.4875 0.5125 6 1 1 0.0651 0.9349 7 1 0 * 0.8742 0.1258 8 1 0 * 0.9072 0.0928 9 1 1 0.3037 0.6963 10 0 0 0.8998 0.1002 11 0 0 0.7164 0.2836 12 0 0 0.7868 0.2132 13 0 0 0.9127 0.0873 14 1 1 0.1599 0.8401

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15 0 0 0.7840 0.2160 16 1 1 0.0310 0.9690 17 1 1 0.4281 0.5719 18 0 0 0.7455 0.2545 19 0 0 0.9433 0.0567 20 1 1 0.3627 0.6373 21 0 0 0.5895 0.4105 22 0 0 0.8462 0.1538 23 1 0 * 0.5258 0.4742 24 0 0 0.7953 0.2047 25 1 1 0.0716 0.9284 26 1 1 0.1808 0.8192 27 0 0 0.7362 0.2638 28 1 1 0.1359 0.8641

18:24 Saturday, November 21, 2009 310 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.9062 0.0938 30 0 0 0.8753 0.1247 31 0 0 0.9099 0.0901 32 0 0 0.8392 0.1608 33 1 0 * 0.8989 0.1011 34 0 1 * 0.3267 0.6733 35 1 1 0.0476 0.9524 36 1 1 0.0680 0.9320 37 0 0 0.8826 0.1174 38 0 0 0.6686 0.3314 39 0 0 0.9261 0.0739 40 0 1 * 0.3982 0.6018 41 1 1 0.0540 0.9460 42 0 0 0.7114 0.2886 43 0 1 * 0.2646 0.7354 44 1 1 0.0105 0.9895 45 1 1 0.1688 0.8312 46 0 1 * 0.4374 0.5626 47 1 0 * 0.8989 0.1011 48 1 1 0.0104 0.9896 49 0 0 0.6051 0.3949 50 0 0 0.9122 0.0878 51 0 0 0.8667 0.1333 52 0 0 0.7894 0.2106 53 0 0 0.6885 0.3115 54 1 0 * 0.5776 0.4224 55 1 1 0.1473 0.8527 56 1 1 0.0887 0.9113 57 1 1 0.2127 0.7873 58 1 1 0.0104 0.9896 59 1 1 0.0540 0.9460 60 1 1 0.1761 0.8239 61 0 0 0.7213 0.2787 62 1 1 0.0322 0.9678 63 1 1 0.1731 0.8269 64 1 0 * 0.9118 0.0882 65 1 1 0.1075 0.8925 66 1 1 0.0322 0.9678 67 0 0 0.8163 0.1837 68 0 0 0.7929 0.2071

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69 0 0 0.8659 0.1341

18:24 Saturday, November 21, 2009 311 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 0 * 0.8377 0.1623

* Misclassified observation

18:24 Saturday, November 21, 2009 312 Classification Analysis on Coast using PCT1 and PCT2 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 28 4 32 87.50 12.50 100.00

1 10 28 38 26.32 73.68 100.00

Total 38 32 70 54.29 45.71 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1250 0.2632 0.1941 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 313 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

Page 181: R Code for Calculating Beale’s F-Type Statistic: c1

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 2 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

18:24 Saturday, November 21, 2009 314 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.8261 0.1739 2 1 0 * 0.6404 0.3596 3 1 1 0.0000 1.0000 4 1 1 0.0000 1.0000 5 1 0 * 0.6404 0.3596 6 1 1 0.0000 1.0000 7 1 0 * 0.6404 0.3596 8 1 1 0.2289 0.7711 9 1 1 0.2289 0.7711 10 0 0 0.8261 0.1739 11 0 0 1.0000 0.0000 12 0 0 0.8261 0.1739 13 0 1 * 0.4419 0.5581 14 1 1 0.0000 1.0000 15 0 0 1.0000 0.0000 16 1 1 0.0000 1.0000 17 1 1 0.4419 0.5581 18 0 0 1.0000 0.0000 19 0 0 0.6404 0.3596 20 1 0 * 0.6404 0.3596 21 0 0 0.8261 0.1739 22 0 0 0.8261 0.1739 23 1 0 * 0.6404 0.3596 24 0 0 0.8261 0.1739 25 1 1 0.0000 1.0000

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26 1 1 0.0000 1.0000 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 315 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 1 0.0000 1.0000 29 1 1 0.4419 0.5581 30 0 1 * 0.4419 0.5581 31 0 1 * 0.4419 0.5581 32 0 0 0.6404 0.3596 33 1 1 0.4419 0.5581 34 0 1 * 0.4419 0.5581 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 0 0.6404 0.3596 38 0 0 1.0000 0.0000 39 0 0 0.7037 0.2963 40 0 0 0.6404 0.3596 41 1 1 0.0000 1.0000 42 0 0 0.6404 0.3596 43 0 1 * 0.4419 0.5581 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 1 * 0.4419 0.5581 47 1 1 0.4419 0.5581 48 1 1 0.0000 1.0000 49 0 0 0.8261 0.1739 50 0 0 0.6404 0.3596 51 0 1 * 0.4419 0.5581 52 0 1 * 0.4419 0.5581 53 0 0 0.8261 0.1739 54 1 1 0.4419 0.5581 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.0000 1.0000 58 1 1 0.0000 1.0000 59 1 1 0.0000 1.0000 60 1 1 0.2289 0.7711 61 0 0 1.0000 0.0000 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 1 0.4419 0.5581 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 0.8261 0.1739 68 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 316 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

Page 183: R Code for Calculating Beale’s F-Type Statistic: c1

From Classified Obs coast into coast 0 1

69 0 1 * 0.3725 0.6275 70 1 0 * 0.6404 0.3596

* Misclassified observation

18:24 Saturday, November 21, 2009 317 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 23 9 32 71.88 28.13 100.00

1 6 32 38 15.79 84.21 100.00

Total 29 41 70 41.43 58.57 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.2813 0.1579 0.2196 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 318 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Page 184: R Code for Calculating Beale’s F-Type Statistic: c1

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.8306 0.1694 2 1 0 * 0.5362 0.4638 3 1 1 0.0000 1.0000 4 1 1 0.0000 1.0000 5 1 0 * 0.8222 0.1778 6 1 1 0.0000 1.0000 7 1 0 * 0.8222 0.1778 8 1 1 0.4353 0.5647 9 1 1 0.4353 0.5647 10 0 0 0.6477 0.3523 11 0 0 1.0000 0.0000 12 0 0 0.6477 0.3523 13 0 1 * 0.4497 0.5503 14 1 1 0.2242 0.7758 15 0 0 1.0000 0.0000 16 1 1 0.0000 1.0000 17 1 1 0.4353 0.5647 18 0 0 1.0000 0.0000 19 0 0 0.6477 0.3523 20 1 0 * 0.6343 0.3657 21 0 0 0.6477 0.3523 22 0 0 0.8306 0.1694 23 1 0 * 0.6343 0.3657 24 0 0 0.6477 0.3523 25 1 1 0.0000 1.0000 26 1 1 0.0000 1.0000 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 319 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 1 0.0000 1.0000 29 1 0 * 0.6343 0.3657 30 0 1 * 0.4497 0.5503 31 0 1 * 0.4497 0.5503 32 0 0 0.6477 0.3523 33 1 0 * 0.6343 0.3657 34 0 1 * 0.2346 0.7654 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 0 0.6477 0.3523 38 0 0 1.0000 0.0000 39 0 0 0.6477 0.3523 40 0 0 0.6477 0.3523

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41 1 1 0.0000 1.0000 42 0 0 0.6477 0.3523 43 0 1 * 0.4497 0.5503 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 1 * 0.4497 0.5503 47 1 0 * 0.6343 0.3657 48 1 1 0.0000 1.0000 49 0 0 0.8306 0.1694 50 0 0 0.6477 0.3523 51 0 1 * 0.4497 0.5503 52 0 1 * 0.4497 0.5503 53 0 0 0.8306 0.1694 54 1 0 * 0.6343 0.3657 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.2242 0.7758 58 1 1 0.0000 1.0000 59 1 1 0.0000 1.0000 60 1 1 0.2242 0.7758 61 0 0 1.0000 0.0000 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 0 * 0.6343 0.3657 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 0.8306 0.1694 68 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 320 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 1 * 0.2346 0.7654 70 1 0 * 0.8222 0.1778

* Misclassified observation

18:24 Saturday, November 21, 2009 321 Classification Analysis on Coast using PCT1 and PCT2 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Page 186: R Code for Calculating Beale’s F-Type Statistic: c1

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 23 9 32 71.88 28.13 100.00

1 11 27 38 28.95 71.05 100.00

Total 34 36 70 48.57 51.43 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.2813 0.2895 0.2854 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 322 Classification Analysis on Coast using PCT1 and PCT2 Logistic Regression

The LOGISTIC Procedure

Model Information

Data Set WORK.PCCOMB Response Variable coast Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring

Number of Observations Read 70 Number of Observations Used 70

Response Profile

Ordered Total Value coast Frequency

1 0 32 2 1 38

Probability modeled is coast=0.

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

Model Fit Statistics

Intercept Intercept and Criterion Only Covariates

AIC 98.526 68.726 SC 100.774 75.472

Page 187: R Code for Calculating Beale’s F-Type Statistic: c1

-2 Log L 96.526 62.726

Testing Global Null Hypothesis: BETA=0

Test Chi-Square DF Pr > ChiSq

Likelihood Ratio 33.7992 2 <.0001 Score 27.6528 2 <.0001 Wald 18.1149 2 0.0001

18:24 Saturday, November 21, 2009 323 Classification Analysis on Coast using PCT1 and PCT2 Logistic Regression

The LOGISTIC Procedure

Analysis of Maximum Likelihood Estimates

Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq

Intercept 1 -0.4978 0.3531 1.9872 0.1586 PCT1 1 -0.0446 0.0244 3.3261 0.0682 PCT2 1 0.3978 0.1093 13.2511 0.0003

Odds Ratio Estimates

Point 95% Wald Effect Estimate Confidence Limits

PCT1 0.956 0.912 1.003 PCT2 1.489 1.202 1.844

Association of Predicted Probabilities and Observed Responses

Percent Concordant 84.5 Somers' D 0.690 Percent Discordant 15.5 Gamma 0.691 Percent Tied 0.1 Tau-a 0.347 Pairs 1216 c 0.845

18:24 Saturday, November 21, 2009 324 Classification Analysis on Coast using PCT1 and PCT2 Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

1 0 0 0.60796 0.39204 0.60796 2 1 0 0.79819 0.20181 0.79819 3 1 1 0.11486 0.88514 0.11486 4 1 1 0.07621 0.92379 0.07621 5 1 1 0.39753 0.60247 0.39753 6 1 1 0.05443 0.94557 0.05443 7 1 0 0.76446 0.23554 0.76446 8 1 0 0.79486 0.20514 0.79486 9 1 1 0.22716 0.77284 0.22716 10 0 0 0.84345 0.15655 0.84345 11 0 0 0.61687 0.38313 0.61687 12 0 0 0.68208 0.31792 0.68208 13 0 0 0.83717 0.16283 0.83717 14 1 1 0.13002 0.86998 0.13002 15 0 0 0.70678 0.29322 0.70678 16 1 1 0.02831 0.97169 0.02831 17 1 1 0.38924 0.61076 0.38924 18 0 0 0.64661 0.35339 0.64661

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19 0 0 0.89311 0.10689 0.89311 20 1 1 0.30835 0.69165 0.30835 21 0 1 0.48981 0.51019 0.48981 22 0 0 0.76871 0.23129 0.76871 23 1 1 0.44267 0.55733 0.44267 24 0 0 0.68569 0.31431 0.68569 25 1 1 0.06331 0.93669 0.06331 26 1 1 0.13907 0.86093 0.13907 27 0 0 0.64278 0.35722 0.64278 28 1 1 0.11106 0.88894 0.11106 29 1 0 0.83626 0.16374 0.83626 30 0 0 0.80081 0.19919 0.80081 31 0 0 0.87425 0.12575 0.87425 32 0 0 0.77571 0.22429 0.77571 33 1 0 0.82352 0.17648 0.82352 34 0 1 0.25946 0.74054 0.25946 35 1 1 0.04162 0.95838 0.04162 36 1 1 0.05805 0.94195 0.05805 37 0 0 0.89360 0.10640 0.89360 38 0 0 0.57474 0.42526 0.57474 39 0 0 0.88800 0.11200 0.88800 40 0 1 0.37318 0.62682 0.37318 41 1 1 0.02871 0.97129 0.02871 42 0 0 0.65227 0.34773 0.65227 43 0 1 0.25115 0.74885 0.25115 44 1 1 0.01077 0.98923 0.01077 45 1 1 0.10874 0.89126 0.10874 46 0 1 0.37411 0.62589 0.37411 47 1 0 0.82352 0.17648 0.82352 48 1 1 0.00561 0.99439 0.00561

18:24 Saturday, November 21, 2009 325 Classification Analysis on Coast using PCT1 and PCT2 Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

49 0 0 0.54888 0.45112 0.54888 50 0 0 0.86764 0.13236 0.86764 51 0 0 0.81885 0.18115 0.81885 52 0 0 0.84839 0.15161 0.84839 53 0 0 0.56058 0.43942 0.56058 54 1 0 0.52017 0.47983 0.52017 55 1 1 0.09203 0.90797 0.09203 56 1 1 0.07804 0.92196 0.07804 57 1 1 0.14489 0.85511 0.14489 58 1 1 0.00561 0.99439 0.00561 59 1 1 0.02871 0.97129 0.02871 60 1 1 0.14859 0.85141 0.14859 61 0 0 0.65115 0.34885 0.65115 62 1 1 0.02915 0.97085 0.02915 63 1 1 0.11057 0.88943 0.11057 64 1 0 0.81068 0.18932 0.81068 65 1 1 0.03990 0.96010 0.03990 66 1 1 0.02915 0.97085 0.02915 67 0 0 0.72631 0.27369 0.72631 68 0 0 0.70889 0.29111 0.70889 69 0 0 0.82434 0.17566 0.82434 70 1 0 0.69266 0.30734 0.69266

18:24 Saturday, November 21, 2009 326 Classification Analysis on Coast using PCT1 and PCT2 Logistic Regression

The FREQ Procedure

Table of coast by predict

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coast predict

Frequency‚ Percent ‚ Row Pct ‚ Col Pct ‚ 0‚ 1‚ Total ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 0 ‚ 27 ‚ 5 ‚ 32 ‚ 38.57 ‚ 7.14 ‚ 45.71 ‚ 84.38 ‚ 15.63 ‚ ‚ 75.00 ‚ 14.71 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 1 ‚ 9 ‚ 29 ‚ 38 ‚ 12.86 ‚ 41.43 ‚ 54.29 ‚ 23.68 ‚ 76.32 ‚ ‚ 25.00 ‚ 85.29 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ Total 36 34 70 51.43 48.57 100.00

18:24 Saturday, November 21, 2009 327 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 4 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

Pooled Covariance Matrix Information

Natural Log of the Covariance Determinant of the Matrix Rank Covariance Matrix

4 14.20741

18:24 Saturday, November 21, 2009 328 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure

Pairwise Generalized Squared Distances Between Groups

2 _ _ -1 _ _ D (i|j) = (X - X )' COV (X - X ) i j i j

Generalized Squared Distance to coast

From coast 0 1

0 0 1.47779

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1 1.47779 0

Linear Discriminant Function

_ -1 _ -1 _ Constant = -.5 X' COV X Coefficient Vector = COV X j j j

Linear Discriminant Function for coast

Variable 0 1

Constant -0.21775 -0.15441 PCO1 0.04755 -0.04005 PCO2 -0.05328 0.04486 PCO3 -0.08207 0.06911 PCO4 -0.04274 0.03599

18:24 Saturday, November 21, 2009 329 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.8595 0.1405 2 1 0 * 0.9520 0.0480 3 1 0 * 0.7219 0.2781 4 1 1 0.0624 0.9376 5 1 1 0.1656 0.8344 6 1 1 0.1900 0.8100 7 1 0 * 0.6367 0.3633 8 1 0 * 0.6021 0.3979 9 1 0 * 0.8791 0.1209 10 0 0 0.5464 0.4536 11 0 0 0.8349 0.1651 12 0 0 0.8624 0.1376 13 0 1 * 0.3946 0.6054 14 1 1 0.3861 0.6139 15 0 0 0.8819 0.1181 16 1 1 0.0519 0.9481 17 1 1 0.3286 0.6714 18 0 0 0.8401 0.1599 19 0 1 * 0.4773 0.5227 20 1 1 0.2935 0.7065 21 0 0 0.8309 0.1691 22 0 0 0.8291 0.1709 23 1 1 0.1856 0.8144

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24 0 0 0.8756 0.1244 25 1 1 0.1019 0.8981 26 1 1 0.2244 0.7756 27 0 0 0.7859 0.2141 28 1 0 * 0.5060 0.4940

18:24 Saturday, November 21, 2009 330 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.8445 0.1555 30 0 0 0.7711 0.2289 31 0 0 0.5022 0.4978 32 0 0 0.7400 0.2600 33 1 1 0.3406 0.6594 34 0 0 0.5508 0.4492 35 1 1 0.1697 0.8303 36 1 1 0.0985 0.9015 37 0 1 * 0.2461 0.7539 38 0 0 0.8034 0.1966 39 0 1 * 0.4997 0.5003 40 0 1 * 0.3912 0.6088 41 1 1 0.3061 0.6939 42 0 0 0.7388 0.2612 43 0 0 0.6725 0.3275 44 1 1 0.1267 0.8733 45 1 1 0.2099 0.7901 46 0 1 * 0.3109 0.6891 47 1 0 * 0.8989 0.1011 48 1 1 0.1859 0.8141 49 0 1 * 0.3721 0.6279 50 0 1 * 0.4048 0.5952 51 0 0 0.6574 0.3426 52 0 1 * 0.4383 0.5617 53 0 0 0.8175 0.1825 54 1 1 0.3116 0.6884 55 1 1 0.1893 0.8107 56 1 1 0.0656 0.9344 57 1 1 0.4738 0.5262 58 1 1 0.2320 0.7680 59 1 1 0.1409 0.8591 60 1 1 0.3725 0.6275 61 0 0 0.7653 0.2347 62 1 1 0.1549 0.8451 63 1 1 0.2181 0.7819 64 1 0 * 0.5889 0.4111 65 1 1 0.2714 0.7286 66 1 1 0.1298 0.8702 67 0 0 0.8936 0.1064 68 0 0 0.7573 0.2427 69 0 1 * 0.4736 0.5264

18:24 Saturday, November 21, 2009 331 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB

Page 192: R Code for Calculating Beale’s F-Type Statistic: c1

Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 0 * 0.6913 0.3087

* Misclassified observation

18:24 Saturday, November 21, 2009 332 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 22 10 32 68.75 31.25 100.00

1 10 28 38 26.32 73.68 100.00

Total 32 38 70 45.71 54.29 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.3125 0.2632 0.2878 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 333 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X )

Page 193: R Code for Calculating Beale’s F-Type Statistic: c1

j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.8537 0.1463 2 1 0 * 0.9779 0.0221 3 1 0 * 0.7933 0.2067 4 1 1 0.0620 0.9380 5 1 1 0.2119 0.7881 6 1 1 0.1965 0.8035 7 1 0 * 0.6569 0.3431 8 1 0 * 0.6450 0.3550 9 1 0 * 0.9395 0.0605 10 0 0 0.5321 0.4679 11 0 0 0.8293 0.1707 12 0 0 0.8570 0.1430 13 0 1 * 0.3546 0.6454 14 1 1 0.4278 0.5722 15 0 0 0.8782 0.1218 16 1 1 0.0497 0.9503 17 1 1 0.3737 0.6263 18 0 0 0.8343 0.1657 19 0 1 * 0.4406 0.5594 20 1 1 0.3064 0.6936 21 0 0 0.8144 0.1856 22 0 0 0.8151 0.1849 23 1 1 0.2244 0.7756 24 0 0 0.8666 0.1334 25 1 1 0.1049 0.8951 26 1 1 0.2399 0.7601 27 0 0 0.7667 0.2333 28 1 0 * 0.5497 0.4503

18:24 Saturday, November 21, 2009 334 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.8877 0.1123 30 0 0 0.7604 0.2396 31 0 1 * 0.4862 0.5138 32 0 0 0.7338 0.2662 33 1 1 0.3619 0.6381 34 0 0 0.5412 0.4588 35 1 1 0.1756 0.8244 36 1 1 0.1020 0.8980 37 0 1 * 0.1826 0.8174 38 0 0 0.7898 0.2102 39 0 1 * 0.4744 0.5256 40 0 1 * 0.3416 0.6584

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41 1 1 0.3124 0.6876 42 0 0 0.7319 0.2681 43 0 0 0.6428 0.3572 44 1 1 0.1395 0.8605 45 1 1 0.2231 0.7769 46 0 1 * 0.2828 0.7172 47 1 0 * 0.9270 0.0730 48 1 1 0.1951 0.8049 49 0 1 * 0.2812 0.7188 50 0 1 * 0.3323 0.6677 51 0 0 0.6191 0.3809 52 0 1 * 0.3940 0.6060 53 0 0 0.8110 0.1890 54 1 1 0.3297 0.6703 55 1 1 0.1976 0.8024 56 1 1 0.0658 0.9342 57 1 1 0.4944 0.5056 58 1 1 0.2466 0.7534 59 1 1 0.1468 0.8532 60 1 1 0.3935 0.6065 61 0 0 0.7605 0.2395 62 1 1 0.1628 0.8372 63 1 1 0.2248 0.7752 64 1 0 * 0.6296 0.3704 65 1 1 0.2855 0.7145 66 1 1 0.1357 0.8643 67 0 0 0.8872 0.1128 68 0 0 0.7282 0.2718 69 0 1 * 0.4162 0.5838

18:24 Saturday, November 21, 2009 335 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 0 * 0.7384 0.2616

* Misclassified observation

18:24 Saturday, November 21, 2009 336 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Page 195: R Code for Calculating Beale’s F-Type Statistic: c1

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 21 11 32 65.63 34.38 100.00

1 10 28 38 26.32 73.68 100.00

Total 31 39 70 44.29 55.71 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.3438 0.2632 0.3035 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 337 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 4 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

18:24 Saturday, November 21, 2009 338 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

Page 196: R Code for Calculating Beale’s F-Type Statistic: c1

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 0 * 0.6404 0.3596 3 1 0 * 0.6404 0.3596 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 1 0.2289 0.7711 7 1 0 * 0.6404 0.3596 8 1 1 0.4419 0.5581 9 1 0 * 0.6404 0.3596 10 0 0 0.6404 0.3596 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 1 * 0.4419 0.5581 14 1 1 0.4419 0.5581 15 0 0 0.8261 0.1739 16 1 1 0.0000 1.0000 17 1 1 0.4419 0.5581 18 0 0 1.0000 0.0000 19 0 0 0.8261 0.1739 20 1 0 * 0.8261 0.1739 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 1.0000 0.0000 25 1 1 0.0000 1.0000 26 1 1 0.4419 0.5581 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 339 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 1 0.4419 0.5581 29 1 0 * 0.8261 0.1739 30 0 0 0.6404 0.3596 31 0 0 0.6404 0.3596 32 0 0 1.0000 0.0000 33 1 1 0.2289 0.7711 34 0 0 0.8261 0.1739 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 0 0.6404 0.3596 38 0 0 1.0000 0.0000 39 0 1 * 0.4419 0.5581 40 0 0 0.6404 0.3596 41 1 1 0.4419 0.5581 42 0 0 1.0000 0.0000 43 0 0 0.6404 0.3596 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 1 * 0.4419 0.5581 47 1 0 * 0.6404 0.3596 48 1 1 0.0000 1.0000 49 0 0 0.6404 0.3596 50 0 0 0.8261 0.1739 51 0 0 0.6404 0.3596

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52 0 0 0.8261 0.1739 53 0 0 1.0000 0.0000 54 1 1 0.2289 0.7711 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.4419 0.5581 58 1 1 0.0000 1.0000 59 1 1 0.2289 0.7711 60 1 0 * 0.6404 0.3596 61 0 0 1.0000 0.0000 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 1 0.4419 0.5581 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 1.0000 0.0000 68 0 0 0.6404 0.3596

18:24 Saturday, November 21, 2009 340 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 0.8261 0.1739 70 1 1 0.4419 0.5581

* Misclassified observation

18:24 Saturday, November 21, 2009 341 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 29 3 32 90.63 9.38 100.00

1 8 30 38 21.05 78.95 100.00

Page 198: R Code for Calculating Beale’s F-Type Statistic: c1

Total 37 33 70 52.86 47.14 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.0938 0.2105 0.1521 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 342 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 0 * 0.8222 0.1778 3 1 0 * 0.8222 0.1778 4 1 1 0.0000 1.0000 5 1 1 0.2242 0.7758 6 1 1 0.2242 0.7758 7 1 0 * 0.8222 0.1778 8 1 1 0.4353 0.5647 9 1 0 * 0.8222 0.1778 10 0 1 * 0.4497 0.5503 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 1 * 0.4497 0.5503 14 1 0 * 0.6343 0.3657 15 0 0 0.8306 0.1694 16 1 1 0.0000 1.0000 17 1 0 * 0.6343 0.3657 18 0 0 1.0000 0.0000 19 0 0 0.8306 0.1694 20 1 0 * 0.8222 0.1778 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 1.0000 0.0000 25 1 1 0.0000 1.0000 26 1 1 0.4353 0.5647 27 0 0 1.0000 0.0000

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18:24 Saturday, November 21, 2009 343 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 0 * 0.6343 0.3657 29 1 0 * 0.8222 0.1778 30 0 0 0.6477 0.3523 31 0 1 * 0.4497 0.5503 32 0 0 0.8306 0.1694 33 1 1 0.4353 0.5647 34 0 0 0.6477 0.3523 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 0 0.6477 0.3523 38 0 0 0.8306 0.1694 39 0 1 * 0.4497 0.5503 40 0 0 0.6477 0.3523 41 1 1 0.4353 0.5647 42 0 0 1.0000 0.0000 43 0 0 0.6477 0.3523 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 1 * 0.2346 0.7654 47 1 0 * 0.8222 0.1778 48 1 1 0.0000 1.0000 49 0 0 0.6477 0.3523 50 0 0 0.6477 0.3523 51 0 0 0.6477 0.3523 52 0 0 0.8306 0.1694 53 0 0 0.8306 0.1694 54 1 1 0.2242 0.7758 55 1 1 0.2242 0.7758 56 1 1 0.0000 1.0000 57 1 0 * 0.6343 0.3657 58 1 1 0.0000 1.0000 59 1 1 0.2242 0.7758 60 1 0 * 0.6343 0.3657 61 0 0 0.8306 0.1694 62 1 1 0.0000 1.0000 63 1 1 0.0000 1.0000 64 1 1 0.4353 0.5647 65 1 1 0.2242 0.7758 66 1 1 0.0000 1.0000 67 0 0 1.0000 0.0000 68 0 0 0.6477 0.3523

18:24 Saturday, November 21, 2009 344 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified

Page 200: R Code for Calculating Beale’s F-Type Statistic: c1

Obs coast into coast 0 1

69 0 0 0.8306 0.1694 70 1 0 * 0.6343 0.3657

* Misclassified observation

18:24 Saturday, November 21, 2009 345 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 27 5 32 84.38 15.63 100.00

1 13 25 38 34.21 65.79 100.00

Total 40 30 70 57.14 42.86 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1563 0.3421 0.2492 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 346 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

The LOGISTIC Procedure

Model Information

Data Set WORK.PCCOMB Response Variable coast Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring

Page 201: R Code for Calculating Beale’s F-Type Statistic: c1

Number of Observations Read 70 Number of Observations Used 70

Response Profile

Ordered Total Value coast Frequency

1 0 32 2 1 38

Probability modeled is coast=0.

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

Model Fit Statistics

Intercept Intercept and Criterion Only Covariates

AIC 98.526 85.068 SC 100.774 96.310 -2 Log L 96.526 75.068

Testing Global Null Hypothesis: BETA=0

Test Chi-Square DF Pr > ChiSq

Likelihood Ratio 21.4579 4 0.0003 Score 19.1840 4 0.0007 Wald 15.2237 4 0.0043

18:24 Saturday, November 21, 2009 347 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

The LOGISTIC Procedure

Analysis of Maximum Likelihood Estimates

Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq

Intercept 1 -0.2437 0.2868 0.7219 0.3955 PCO1 1 0.0895 0.0355 6.3396 0.0118 PCO2 1 -0.0865 0.0381 5.1565 0.0232 PCO3 1 -0.1385 0.0535 6.7067 0.0096 PCO4 1 -0.0840 0.0842 0.9954 0.3184

Odds Ratio Estimates

Point 95% Wald Effect Estimate Confidence Limits

PCO1 1.094 1.020 1.172 PCO2 0.917 0.851 0.988 PCO3 0.871 0.784 0.967 PCO4 0.919 0.780 1.084

Page 202: R Code for Calculating Beale’s F-Type Statistic: c1

Association of Predicted Probabilities and Observed Responses

Percent Concordant 81.7 Somers' D 0.633 Percent Discordant 18.3 Gamma 0.633 Percent Tied 0.0 Tau-a 0.319 Pairs 1216 c 0.817

18:24 Saturday, November 21, 2009 348 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

1 0 0 0.81644 0.18356 0.81644 2 1 0 0.93471 0.06529 0.93471 3 1 0 0.65828 0.34172 0.65828 4 1 1 0.05431 0.94569 0.05431 5 1 1 0.15831 0.84169 0.15831 6 1 1 0.17600 0.82400 0.17600 7 1 0 0.59544 0.40456 0.59544 8 1 0 0.56774 0.43226 0.56774 9 1 0 0.85025 0.14975 0.85025 10 0 1 0.49068 0.50932 0.49068 11 0 0 0.78394 0.21606 0.78394 12 0 0 0.81837 0.18163 0.81837 13 0 1 0.37140 0.62860 0.37140 14 1 1 0.31765 0.68235 0.31765 15 0 0 0.84887 0.15113 0.84887 16 1 1 0.04188 0.95812 0.04188 17 1 1 0.30404 0.69596 0.30404 18 0 0 0.79181 0.20819 0.79181 19 0 1 0.46486 0.53514 0.46486 20 1 1 0.28345 0.71655 0.28345 21 0 0 0.76451 0.23549 0.76451 22 0 0 0.76759 0.23241 0.76759 23 1 1 0.18556 0.81444 0.18556 24 0 0 0.83062 0.16938 0.83062 25 1 1 0.08981 0.91019 0.08981 26 1 1 0.21292 0.78708 0.21292 27 0 0 0.71278 0.28722 0.71278 28 1 1 0.44190 0.55810 0.44190 29 1 0 0.82652 0.17348 0.82652 30 0 0 0.72580 0.27420 0.72580 31 0 1 0.48055 0.51945 0.48055 32 0 0 0.68403 0.31597 0.68403 33 1 1 0.30879 0.69121 0.30879 34 0 1 0.49732 0.50268 0.49732 35 1 1 0.15141 0.84859 0.15141 36 1 1 0.08201 0.91799 0.08201 37 0 1 0.25008 0.74992 0.25008 38 0 0 0.74547 0.25453 0.74547 39 0 1 0.43319 0.56681 0.43319 40 0 1 0.36223 0.63777 0.36223 41 1 1 0.28908 0.71092 0.28908 42 0 0 0.67957 0.32043 0.67957 43 0 0 0.60909 0.39091 0.60909 44 1 1 0.10363 0.89637 0.10363 45 1 1 0.20276 0.79724 0.20276 46 0 1 0.29836 0.70164 0.29836 47 1 0 0.87048 0.12952 0.87048 48 1 1 0.16796 0.83204 0.16796

18:24 Saturday, November 21, 2009 349 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

Page 203: R Code for Calculating Beale’s F-Type Statistic: c1

49 0 1 0.36779 0.63221 0.36779 50 0 1 0.33359 0.66641 0.33359 51 0 0 0.64945 0.35055 0.64945 52 0 1 0.43006 0.56994 0.43006 53 0 0 0.77973 0.22027 0.77973 54 1 1 0.30754 0.69246 0.30754 55 1 1 0.17630 0.82370 0.17630 56 1 1 0.05673 0.94327 0.05673 57 1 1 0.46031 0.53969 0.46031 58 1 1 0.20756 0.79244 0.20756 59 1 1 0.14304 0.85696 0.14304 60 1 1 0.34281 0.65719 0.34281 61 0 0 0.71468 0.28532 0.71468 62 1 1 0.13599 0.86401 0.13599 63 1 1 0.20249 0.79751 0.20249 64 1 0 0.54174 0.45826 0.54174 65 1 1 0.23510 0.76490 0.23510 66 1 1 0.11497 0.88503 0.11497 67 0 0 0.84881 0.15119 0.84881 68 0 0 0.74519 0.25481 0.74519 69 0 1 0.45743 0.54257 0.45743 70 1 0 0.64627 0.35373 0.64627

18:24 Saturday, November 21, 2009 350 Classification Analysis on Coast using PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

The FREQ Procedure

Table of coast by predict

coast predict

Frequency‚ Percent ‚ Row Pct ‚ Col Pct ‚ 0‚ 1‚ Total ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 0 ‚ 19 ‚ 13 ‚ 32 ‚ 27.14 ‚ 18.57 ‚ 45.71 ‚ 59.38 ‚ 40.63 ‚ ‚ 67.86 ‚ 30.95 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 1 ‚ 9 ‚ 29 ‚ 38 ‚ 12.86 ‚ 41.43 ‚ 54.29 ‚ 23.68 ‚ 76.32 ‚ ‚ 32.14 ‚ 69.05 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ Total 28 42 70 40.00 60.00 100.00

18:24 Saturday, November 21, 2009 351 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 6 DF Within Classes 68 Classes 2 DF Between Classes 1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

Page 204: R Code for Calculating Beale’s F-Type Statistic: c1

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

Pooled Covariance Matrix Information

Natural Log of the Covariance Determinant of the Matrix Rank Covariance Matrix

6 21.13766

18:24 Saturday, November 21, 2009 352 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure

Pairwise Generalized Squared Distances Between Groups

2 _ _ -1 _ _ D (i|j) = (X - X )' COV (X - X ) i j i j

Generalized Squared Distance to coast

From coast 0 1

0 0 3.35059 1 3.35059 0

Linear Discriminant Function

_ -1 _ -1 _ Constant = -.5 X' COV X Coefficient Vector = COV X j j j

Linear Discriminant Function for coast

Variable 0 1

Constant -0.49370 -0.35010 PCT1 -0.04679 0.03940 PCT2 0.25256 -0.21268 PCO1 -0.03908 0.03291 PCO2 -0.01878 0.01581 PCO3 -0.06205 0.05225 PCO4 -0.04034 0.03397

18:24 Saturday, November 21, 2009 353 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

Page 205: R Code for Calculating Beale’s F-Type Statistic: c1

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.8090 0.1910 2 1 0 * 0.9382 0.0618 3 1 1 0.3952 0.6048 4 1 1 0.1090 0.8910 5 1 1 0.0747 0.9253 6 1 1 0.0431 0.9569 7 1 0 * 0.9018 0.0982 8 1 0 * 0.7422 0.2578 9 1 0 * 0.6135 0.3865 10 0 0 0.9196 0.0804 11 0 0 0.8756 0.1244 12 0 0 0.8753 0.1247 13 0 0 0.9502 0.0498 14 1 1 0.3073 0.6927 15 0 0 0.8361 0.1639 16 1 1 0.0232 0.9768 17 1 1 0.4860 0.5140 18 0 0 0.8364 0.1636 19 0 0 0.9495 0.0505 20 1 1 0.1704 0.8296 21 0 0 0.8488 0.1512 22 0 0 0.9289 0.0711 23 1 1 0.0679 0.9321 24 0 0 0.8988 0.1012 25 1 1 0.0670 0.9330 26 1 1 0.0855 0.9145 27 0 0 0.8714 0.1286 28 1 1 0.3268 0.6732

18:24 Saturday, November 21, 2009 354 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.8111 0.1889 30 0 0 0.9257 0.0743 31 0 0 0.8942 0.1058 32 0 0 0.9468 0.0532 33 1 0 * 0.8647 0.1353 34 0 1 * 0.4812 0.5188 35 1 1 0.0388 0.9612 36 1 1 0.1129 0.8871 37 0 0 0.6666 0.3334 38 0 0 0.8568 0.1432 39 0 0 0.9776 0.0224 40 0 0 0.5041 0.4959 41 1 1 0.0154 0.9846 42 0 0 0.8680 0.1320 43 0 0 0.5643 0.4357

Page 206: R Code for Calculating Beale’s F-Type Statistic: c1

44 1 1 0.0128 0.9872 45 1 1 0.0261 0.9739 46 0 1 * 0.2492 0.7508 47 1 0 * 0.9228 0.0772 48 1 1 0.0065 0.9935 49 0 0 0.6376 0.3624 50 0 0 0.9617 0.0383 51 0 0 0.7563 0.2437 52 0 0 0.6644 0.3356 53 0 0 0.6420 0.3580 54 1 1 0.1642 0.8358 55 1 1 0.0381 0.9619 56 1 1 0.0559 0.9441 57 1 1 0.0614 0.9386 58 1 1 0.0076 0.9924 59 1 1 0.0092 0.9908 60 1 1 0.2013 0.7987 61 0 0 0.8527 0.1473 62 1 1 0.0183 0.9817 63 1 1 0.0561 0.9439 64 1 0 * 0.8093 0.1907 65 1 1 0.1329 0.8671 66 1 1 0.0168 0.9832 67 0 0 0.9201 0.0799 68 0 0 0.6505 0.3495 69 0 0 0.9248 0.0752

18:24 Saturday, November 21, 2009 355 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 0 * 0.8627 0.1373

* Misclassified observation

18:24 Saturday, November 21, 2009 356 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j j j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

Page 207: R Code for Calculating Beale’s F-Type Statistic: c1

From coast 0 1 Total

0 30 2 32 93.75 6.25 100.00

1 9 29 38 23.68 76.32 100.00

Total 39 31 70 55.71 44.29 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.0625 0.2368 0.1497 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 357 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 0.7897 0.2103 2 1 0 * 0.9770 0.0230 3 1 1 0.4933 0.5067 4 1 1 0.1298 0.8702 5 1 1 0.1009 0.8991 6 1 1 0.0448 0.9552 7 1 0 * 0.9337 0.0663 8 1 0 * 0.8020 0.1980 9 1 0 * 0.7648 0.2352 10 0 0 0.9132 0.0868 11 0 0 0.8681 0.1319 12 0 0 0.8656 0.1344 13 0 0 0.9397 0.0603 14 1 1 0.3580 0.6420 15 0 0 0.8181 0.1819 16 1 1 0.0228 0.9772 17 1 0 * 0.5890 0.4110 18 0 0 0.8241 0.1759 19 0 0 0.9409 0.0591 20 1 1 0.1876 0.8124 21 0 0 0.8224 0.1776

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22 0 0 0.9213 0.0787 23 1 1 0.0830 0.9170 24 0 0 0.8845 0.1155 25 1 1 0.0717 0.9283 26 1 1 0.0933 0.9067 27 0 0 0.8541 0.1459 28 1 1 0.3718 0.6282

18:24 Saturday, November 21, 2009 358 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

29 1 0 * 0.8760 0.1240 30 0 0 0.9209 0.0791 31 0 0 0.8853 0.1147 32 0 0 0.9443 0.0557 33 1 0 * 0.9303 0.0697 34 0 1 * 0.4595 0.5405 35 1 1 0.0402 0.9598 36 1 1 0.1283 0.8717 37 0 1 * 0.4832 0.5168 38 0 0 0.8405 0.1595 39 0 0 0.9770 0.0230 40 0 1 * 0.4410 0.5590 41 1 1 0.0148 0.9852 42 0 0 0.8617 0.1383 43 0 0 0.5015 0.4985 44 1 1 0.0105 0.9895 45 1 1 0.0265 0.9735 46 0 1 * 0.2119 0.7881 47 1 0 * 0.9521 0.0479 48 1 1 0.0045 0.9955 49 0 0 0.5281 0.4719 50 0 0 0.9562 0.0438 51 0 0 0.7148 0.2852 52 0 1 * 0.4764 0.5236 53 0 0 0.6061 0.3939 54 1 1 0.1923 0.8077 55 1 1 0.0396 0.9604 56 1 1 0.0605 0.9395 57 1 1 0.0660 0.9340 58 1 1 0.0054 0.9946 59 1 1 0.0081 0.9919 60 1 1 0.2189 0.7811 61 0 0 0.8470 0.1530 62 1 1 0.0176 0.9824 63 1 1 0.0586 0.9414 64 1 0 * 0.8643 0.1357 65 1 1 0.1753 0.8247 66 1 1 0.0160 0.9840 67 0 0 0.9103 0.0897 68 0 0 0.5737 0.4263 69 0 0 0.9100 0.0900

18:24 Saturday, November 21, 2009 359 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

Page 209: R Code for Calculating Beale’s F-Type Statistic: c1

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using Linear Discriminant Function

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

70 1 0 * 0.9119 0.0881

* Misclassified observation

18:24 Saturday, November 21, 2009 360 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: Linear Discriminant Function

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using Linear Discriminant Function

Generalized Squared Distance Function

2 _ -1 _ D (X) = (X-X )' COV (X-X ) j (X)j (X) (X)j

Posterior Probability of Membership in Each coast

2 2 Pr(j|X) = exp(-.5 D (X)) / SUM exp(-.5 D (X)) j k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 27 5 32 84.38 15.63 100.00

1 10 28 38 26.32 73.68 100.00

Total 37 33 70 52.86 47.14 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1563 0.2632 0.2097 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 361 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure

Observations 70 DF Total 69 Variables 6 DF Within Classes 68 Classes 2 DF Between Classes 1

Page 210: R Code for Calculating Beale’s F-Type Statistic: c1

Class Level Information

Variable Prior coast Name Frequency Weight Proportion Probability

0 _0 32 32.0000 0.457143 0.500000 1 _1 38 38.0000 0.542857 0.500000

18:24 Saturday, November 21, 2009 362 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 0 * 0.6404 0.3596 3 1 0 * 0.6404 0.3596 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 1 0.0000 1.0000 7 1 0 * 0.6404 0.3596 8 1 0 * 0.6404 0.3596 9 1 1 0.4419 0.5581 10 0 0 0.6404 0.3596 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 0 0.8261 0.1739 14 1 0 * 0.6404 0.3596 15 0 0 0.8261 0.1739 16 1 1 0.0000 1.0000 17 1 0 * 0.6404 0.3596 18 0 0 1.0000 0.0000 19 0 0 0.8261 0.1739 20 1 1 0.2289 0.7711 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 1.0000 0.0000 25 1 1 0.0000 1.0000 26 1 1 0.4419 0.5581 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 363 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

Page 211: R Code for Calculating Beale’s F-Type Statistic: c1

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 1 0.4419 0.5581 29 1 0 * 0.6404 0.3596 30 0 0 0.6404 0.3596 31 0 0 0.8261 0.1739 32 0 0 0.8261 0.1739 33 1 1 0.4419 0.5581 34 0 0 0.6404 0.3596 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 1 * 0.4419 0.5581 38 0 0 1.0000 0.0000 39 0 0 0.6404 0.3596 40 0 0 0.6404 0.3596 41 1 1 0.0000 1.0000 42 0 0 1.0000 0.0000 43 0 1 * 0.4419 0.5581 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 1 * 0.4419 0.5581 47 1 0 * 0.8261 0.1739 48 1 1 0.0000 1.0000 49 0 0 0.6404 0.3596 50 0 0 0.8261 0.1739 51 0 0 0.6404 0.3596 52 0 0 0.6404 0.3596 53 0 0 1.0000 0.0000 54 1 1 0.2289 0.7711 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.2289 0.7711 58 1 1 0.0000 1.0000 59 1 1 0.0000 1.0000 60 1 1 0.4419 0.5581 61 0 0 0.8261 0.1739 62 1 1 0.0000 1.0000 63 1 1 0.2289 0.7711 64 1 0 * 0.6404 0.3596 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 1.0000 0.0000 68 0 0 0.6404 0.3596

18:24 Saturday, November 21, 2009 364 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Resubstitution Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 1.0000 0.0000 70 1 0 * 0.6404 0.3596

Page 212: R Code for Calculating Beale’s F-Type Statistic: c1

* Misclassified observation

18:24 Saturday, November 21, 2009 365 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Resubstitution Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 29 3 32 90.63 9.38 100.00

1 10 28 38 26.32 73.68 100.00

Total 39 31 70 55.71 44.29 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.0938 0.2632 0.1785 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 366 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Page 213: R Code for Calculating Beale’s F-Type Statistic: c1

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

1 0 0 1.0000 0.0000 2 1 0 * 0.8222 0.1778 3 1 0 * 0.6343 0.3657 4 1 1 0.0000 1.0000 5 1 1 0.0000 1.0000 6 1 1 0.2242 0.7758 7 1 0 * 0.8222 0.1778 8 1 0 * 0.8222 0.1778 9 1 1 0.4353 0.5647 10 0 1 * 0.4497 0.5503 11 0 0 1.0000 0.0000 12 0 0 1.0000 0.0000 13 0 0 0.6477 0.3523 14 1 0 * 0.6343 0.3657 15 0 0 0.8306 0.1694 16 1 1 0.0000 1.0000 17 1 0 * 0.6343 0.3657 18 0 0 1.0000 0.0000 19 0 0 0.6477 0.3523 20 1 1 0.4353 0.5647 21 0 0 1.0000 0.0000 22 0 0 1.0000 0.0000 23 1 1 0.0000 1.0000 24 0 0 1.0000 0.0000 25 1 1 0.0000 1.0000 26 1 1 0.4353 0.5647 27 0 0 1.0000 0.0000

18:24 Saturday, November 21, 2009 367 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

28 1 0 * 0.6343 0.3657 29 1 0 * 0.8222 0.1778 30 0 0 0.6477 0.3523 31 0 0 0.8306 0.1694 32 0 0 0.8306 0.1694 33 1 0 * 0.6343 0.3657 34 0 0 0.6477 0.3523 35 1 1 0.0000 1.0000 36 1 1 0.0000 1.0000 37 0 1 * 0.4497 0.5503 38 0 0 1.0000 0.0000 39 0 0 0.6477 0.3523 40 0 0 0.6477 0.3523 41 1 1 0.0000 1.0000 42 0 0 0.8306 0.1694 43 0 1 * 0.4497 0.5503 44 1 1 0.0000 1.0000 45 1 1 0.0000 1.0000 46 0 1 * 0.4497 0.5503 47 1 0 * 1.0000 0.0000

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48 1 1 0.0000 1.0000 49 0 0 0.6477 0.3523 50 0 0 0.8306 0.1694 51 0 0 0.6477 0.3523 52 0 1 * 0.4497 0.5503 53 0 0 0.8306 0.1694 54 1 1 0.2242 0.7758 55 1 1 0.0000 1.0000 56 1 1 0.0000 1.0000 57 1 1 0.2242 0.7758 58 1 1 0.0000 1.0000 59 1 1 0.0000 1.0000 60 1 0 * 0.6343 0.3657 61 0 0 0.8306 0.1694 62 1 1 0.0000 1.0000 63 1 1 0.2242 0.7758 64 1 0 * 0.8222 0.1778 65 1 1 0.0000 1.0000 66 1 1 0.0000 1.0000 67 0 0 1.0000 0.0000 68 0 0 0.6477 0.3523

18:24 Saturday, November 21, 2009 368 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Results for Calibration Data: WORK.PCCOMB Cross-validation Results using 5 Nearest Neighbors

Posterior Probability of Membership in coast

From Classified Obs coast into coast 0 1

69 0 0 0.8306 0.1694 70 1 0 * 0.6343 0.3657

* Misclassified observation

18:24 Saturday, November 21, 2009 369 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 RULE: K Nearest Neighbor

The DISCRIM Procedure Classification Summary for Calibration Data: WORK.PCCOMB Cross-validation Summary using 5 Nearest Neighbors

Squared Distance Function

2 -1 D (X,Y) = (X-Y)' COV (X-Y)

Posterior Probability of Membership in Each coast

m (X) = Proportion of obs in group k in 5 k nearest neighbors of X

Pr(j|X) = m (X) PRIOR / SUM ( m (X) PRIOR ) j j k k k

Number of Observations and Percent Classified into coast

From coast 0 1 Total

0 27 5 32

Page 215: R Code for Calculating Beale’s F-Type Statistic: c1

84.38 15.63 100.00

1 13 25 38 34.21 65.79 100.00

Total 40 30 70 57.14 42.86 100.00

Priors 0.5 0.5

Error Count Estimates for coast

0 1 Total

Rate 0.1563 0.3421 0.2492 Priors 0.5000 0.5000

18:24 Saturday, November 21, 2009 370 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

The LOGISTIC Procedure

Model Information

Data Set WORK.PCCOMB Response Variable coast Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring

Number of Observations Read 70 Number of Observations Used 70

Response Profile

Ordered Total Value coast Frequency

1 0 32 2 1 38

Probability modeled is coast=0.

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

Model Fit Statistics

Intercept Intercept and Criterion Only Covariates

AIC 98.526 67.850 SC 100.774 83.589 -2 Log L 96.526 53.850

Testing Global Null Hypothesis: BETA=0

Test Chi-Square DF Pr > ChiSq

Page 216: R Code for Calculating Beale’s F-Type Statistic: c1

Likelihood Ratio 42.6757 6 <.0001 Score 32.2834 6 <.0001 Wald 15.9235 6 0.0142

18:24 Saturday, November 21, 2009 371 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

The LOGISTIC Procedure

Analysis of Maximum Likelihood Estimates

Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq

Intercept 1 -0.8732 0.4857 3.2325 0.0722 PCT1 1 -0.0820 0.0430 3.6264 0.0569 PCT2 1 0.5831 0.1783 10.6976 0.0011 PCO1 1 -0.0865 0.0673 1.6534 0.1985 PCO2 1 0.00680 0.0607 0.0126 0.9108 PCO3 1 -0.1632 0.0770 4.4861 0.0342 PCO4 1 -0.0139 0.1062 0.0170 0.8961

Odds Ratio Estimates

Point 95% Wald Effect Estimate Confidence Limits

PCT1 0.921 0.847 1.002 PCT2 1.792 1.263 2.541 PCO1 0.917 0.804 1.046 PCO2 1.007 0.894 1.134 PCO3 0.849 0.730 0.988 PCO4 0.986 0.801 1.214

Association of Predicted Probabilities and Observed Responses

Percent Concordant 88.8 Somers' D 0.777 Percent Discordant 11.1 Gamma 0.778 Percent Tied 0.1 Tau-a 0.391 Pairs 1216 c 0.889

18:24 Saturday, November 21, 2009 372 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

1 0 0 0.57903 0.42097 0.57903 2 1 0 0.92329 0.07671 0.92329 3 1 1 0.33917 0.66083 0.33917 4 1 1 0.11274 0.88726 0.11274 5 1 1 0.10196 0.89804 0.10196 6 1 1 0.01764 0.98236 0.01764 7 1 0 0.77711 0.22289 0.77711 8 1 0 0.54451 0.45549 0.54451 9 1 1 0.36266 0.63734 0.36266 10 0 0 0.87164 0.12836 0.87164 11 0 0 0.76384 0.23616 0.76384 12 0 0 0.75608 0.24392 0.75608 13 0 0 0.84699 0.15301 0.84699 14 1 1 0.30315 0.69685 0.30315 15 0 0 0.69185 0.30815 0.69185 16 1 1 0.00943 0.99057 0.00943 17 1 0 0.66473 0.33527 0.66473

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18 0 0 0.71275 0.28725 0.71275 19 0 0 0.88576 0.11424 0.88576 20 1 1 0.07076 0.92924 0.07076 21 0 0 0.82293 0.17707 0.82293 22 0 0 0.85470 0.14530 0.85470 23 1 1 0.07368 0.92632 0.07368 24 0 0 0.67143 0.32857 0.67143 25 1 1 0.04612 0.95388 0.04612 26 1 1 0.07631 0.92369 0.07631 27 0 0 0.79968 0.20032 0.79968 28 1 1 0.24671 0.75329 0.24671 29 1 0 0.71728 0.28272 0.71728 30 0 0 0.79644 0.20356 0.79644 31 0 0 0.88053 0.11947 0.88053 32 0 0 0.91869 0.08131 0.91869 33 1 0 0.71323 0.28677 0.71323 34 0 1 0.31286 0.68714 0.31286 35 1 1 0.01502 0.98498 0.01502 36 1 1 0.06640 0.93360 0.06640 37 0 0 0.63231 0.36769 0.63231 38 0 0 0.85630 0.14370 0.85630 39 0 0 0.96064 0.03936 0.96064 40 0 0 0.54946 0.45054 0.54946 41 1 1 0.00226 0.99774 0.00226 42 0 0 0.84744 0.15256 0.84744 43 0 0 0.54399 0.45601 0.54399 44 1 1 0.00163 0.99837 0.00163 45 1 1 0.00801 0.99199 0.00801 46 0 1 0.18831 0.81169 0.18831 47 1 0 0.89549 0.10451 0.89549 48 1 1 0.00030 0.99970 0.00030

18:24 Saturday, November 21, 2009 373 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

Obs coast predict phat Pcoast Pnoncoast

49 0 0 0.67194 0.32806 0.67194 50 0 0 0.96986 0.03014 0.96986 51 0 0 0.63307 0.36693 0.63307 52 0 0 0.69513 0.30487 0.69513 53 0 1 0.38215 0.61785 0.38215 54 1 1 0.12296 0.87704 0.12296 55 1 1 0.01287 0.98713 0.01287 56 1 1 0.03772 0.96228 0.03772 57 1 1 0.01904 0.98096 0.01904 58 1 1 0.00031 0.99969 0.00031 59 1 1 0.00129 0.99871 0.00129 60 1 1 0.14281 0.85719 0.14281 61 0 0 0.79349 0.20651 0.79349 62 1 1 0.00377 0.99623 0.00377 63 1 1 0.01586 0.98414 0.01586 64 1 0 0.68741 0.31259 0.68741 65 1 1 0.01201 0.98799 0.01201 66 1 1 0.00353 0.99647 0.00353 67 0 0 0.87506 0.12494 0.87506 68 0 0 0.58255 0.41745 0.58255 69 0 0 0.93808 0.06192 0.93808 70 1 0 0.56617 0.43383 0.56617

18:24 Saturday, November 21, 2009 374 Classification Analysis on Coast using PCT1, PCT2, PCO1, PCO2, PCO3, AND PCO4 Logistic Regression

The FREQ Procedure

Page 218: R Code for Calculating Beale’s F-Type Statistic: c1

Table of coast by predict

coast predict

Frequency‚ Percent ‚ Row Pct ‚ Col Pct ‚ 0‚ 1‚ Total ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 0 ‚ 29 ‚ 3 ‚ 32 ‚ 41.43 ‚ 4.29 ‚ 45.71 ‚ 90.63 ‚ 9.38 ‚ ‚ 76.32 ‚ 9.38 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ 1 ‚ 9 ‚ 29 ‚ 38 ‚ 12.86 ‚ 41.43 ‚ 54.29 ‚ 23.68 ‚ 76.32 ‚ ‚ 23.68 ‚ 90.63 ‚ ƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ Total 38 32 70 54.29 45.71 100.00