web service for toxicant trigger valuation · 2014-02-18 · web service for toxicant trigger...

Web Service for toxicant

trigger valuation

SUPERVISOR: DR. WARREN JIN

PRESENTER : SHICHAO DONG(U5135470)

Individual Project Courses in the Research School of Computer Science

Overview

Experiment

On

Models

Web

ServiceModification

Overview

Web

Service

BurrliOZ

NEC

Motivation

Extension

Outline BurrliOZ

Model

Experiment

Web Service

NEC

Model

Experiment

Web Service

Discussion

Future Work

Conclusion

BurrliOZ

BurrliOZ NEC Discussion Future Work Conclusion

Model

Burr Type III Log-Logistic

A statistical software package to help environmental managers to figure out trigger values of toxicant

BurrliOZ


Model

Burr Type III

𝐹 𝑥; 𝜃 = 1 −1

(1+𝑥𝑐)𝑘, x > 0, c > 0, k > 0

𝐹 𝑥; 𝜃 = [1 + (𝑏

𝑥−𝑎)𝑐]−𝑘 , c > 0, k > 0

Original :

Re-rewrite :


BurrliOZ


Model

𝐹𝐿𝐿 𝑥 =1

1 + (𝑒𝜇

𝑥)1/𝜃

Distribution Function :

Log-Logistic


BurrliOZ


Test


BurrliOZ


Test

Features:


BurrliOZ


WebService

Shiny fromBurrliOz2

R Language


BurrliOZ


WebService

Shiny


BurrliOZ


WebService

fromBurrliOz2


BurrliOZ


WebService


BurrliOZ


Data Summary


WebService

BurrliOZ


Setting

WebService


BurrliOZ


Report

Download

Report


WebService

BurrliOZ


Plot

WebService


BurrliOZ



WebService

Setting

NEC


NEC Model

E 𝑌𝑖; 𝑥𝑖 = μ = 𝛼 exp[−𝛽 𝑥𝑖 − 𝛾 𝐼(𝑥𝑖 − 𝛾)]

A Bayesian model for the NEC :

With

𝐼 𝑧 = 1, 𝑧 ≥ 00, 𝑧 ≤ 0

No effect concentration

Model

NEC


Model

E 𝑌𝑖; 𝑥𝑖 = μ = 𝛼 exp[−𝛽 𝑥𝑖 − 𝛾 𝐼(𝑥𝑖 − 𝛾)]

A Bayesian model for the NEC :

With

𝐼 𝑧 = 1, 𝑧 ≥ 00, 𝑧 ≤ 0

α is the response at zero/low − dose concentrationsβ controls the rate of decay in the responseγ is the NEC(no effect concentration)


NEC



WinBUGS OpenBUGS

BUGS = Bayesian inference Using Gibbs Sampling

Test

NEC



Test

NEC


Test

WinBUGS OpenBUGS


WinBUGS OpenBUGS

Result Repeatable No Yes

Code Running No Yes

Running on Linux No Yes

Still update No Yes

Same function Yes yes

NEC


R codeShinyUser

Interface Server Core


WebService

OpenBUGSLibrary

NEC



WebService

NEC


WebService


Discussion

Cannot repeat the result

Comparison

Extension


Discussion


Possible reason: has not updated for yearsOur solution: Using OpenBUGS

Discussion


Parameters

Mean Standard deviation

P2.5 P50 P97.5

Alpha 0.95 0.01 0.92 0.95 0.97

Beta 1188 3139 17 107 12350

Gamma 0.95 0.08 0.01 0.86 1.11

Possible Reasons: Typo Error, Software problemSolution : continue using OpenBUGS

Discussion

BurrliOZ BurrliOZ(WEB) NEC NEC(WEB)

Interface Yes Yes No Yes

OS Windows Any Any Any

Platform Computer Computer,mobile device

Computer Computer,mobile device

Software .net library Web Browser WinBUGS Web Browser

Programming No No Yes NO


Comparison

More flexible and accessible usage

Discussion

Features BurrliOZ BurrliOZ(WEB) NEC NEC(WEB)

Loading data

Models 2 3 1 1

Priors distribution NA NA 1 2

Email

Output result


Extension Features

More features and more comparison

Future Work

update the BurrliOZ package;

improve the performance of BurrliOZ;

more possible priors distributions in NEC.

rewriting the front-end by using JavaScript;

testing new possible models;

comparing NOEC. vs NEC or other models

using different tools and packages;

using the same way in different fields


Conclusion

Revisiting and experimenting Shao’s and Fox’s work, and we find there seems to be different from Fox’s result with ours, we try to explain the difference and give our own solutions;

implementing BurrliOZ into web service;

implementing NEC into web service;

providing figures with published quality

extending Fox’s work via providing more flexibility in the web service like normal distribution and Weibull distribution


ExperimentWeb

ServiceExtension

Reference [1] Tom Aldenberg and Wouter Slob. Confidence limits for hazardous concentrations based on logistically distributed noec toxicity data. Ecotoxicology and

Environmental Safety, 25(1):48–63, 1993.

[2] Christophe Andrieu, Nando De Freitas, Arnaud Doucet, and Michael I Jordan. An introduction to mcmc for machine learning. Machine learning, 50(1-2):5–43, 2003.

[3] Kenneth E Biesinger, Leroy E Anderson, and John G Eaton. Chronic effects of inorganic and organic mercury ondaphnia magna: Toxicity, accumulation, and loss. Archives of environmental contamination and toxicology, 11(6):769–774,1982.

[4] MRC Biostatistics. Background to bugs. http://www.mrc-bsu.cam.ac.uk/bugs/.

[5] Irving W Burr. Cumulative frequency functions. The Annals of Mathematical Statistics, 13(2):215–232, 1942.

[6] CSIRO. Burrlioz 2.0 updates. http://www.cmis.csiro.au/Envir/Burrlioz/.

[7] CSIRO. Burrlioz statistical software: a flexible approach to species protection.http://www.csiro.au/Outcomes/Environment/Australian-Landscapes/BurrliOZ.aspx.

[8] A.J. Culyer. The Dictionary of Health Economics. Elgar Original Reference Series. Edward Elgar Publishing, Incorporated, 2005.

[9] David R Fox. A bayesian approach for determining the no effect concentration and hazardous concentration in ecotoxicology. Ecotoxicology and Environmental Safety, 73(2):123–131, 2010.

[10] Jeffrey H Gove, Mark J Ducey, William B Leak, and Lianjun Zhang. Rotated sigmoid structures in managed uneven-aged northern hardwood stands: a look at the burr type iii distribution. Forestry, 81(2):161–176, 2008.

[11] SR Lindsay, GR Wood, and RC Woollons. Modelling the diameter distribution of forest stands using the burr distribution. Journal of Applied Statistics, 23(6):609–620, 1996.

[12] Ana M Pires, João A Branco, Ana Picado, and Elsa Mendonça. Models for the estimation of a no effect concentration. Environmetrics, 13(1):15–27, 2002.

[13] r project. Introduction to r. http://www.r-project.org/.

[14] B.K. Shah and P.H. Dave. A note on log-logistic distribution. Journal of the MS University of Baroda (Science Number), 12:15–20, 1963.

[15] Quanxi Shao. Estimation for hazardous concentrations based on noec toxicity data: an alternative approach. Environmetrics, 11(5):583–595, 2000.

[16] Pandu R Tadikamalla. A look at the burr and related distributions. International Statistical Review/Revue Internationale de Statistique, pages 337–344, 1980.

[17] Pandu R Tadikamalla and Norman L Johnson. Systems of frequency curves generated by transformations of logistic variables. Biometrika, 69(2):461–465, 1982.

[18] Neal Thomas. Changes between winbugs and openbugs. http://www. openbugs.info/w.cgi/OpenVsWin.

[19] Neal Thomas. How it works. http://www.openbugs.info/w/.

[20] Waloddi Weibull et al. A statistical distribution function of wide applicability. Journal of applied mechanics, 18(3):293–297, 1951.

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web service for toxicant trigger valuation · 2014-02-18 · web service for toxicant trigger...

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