springer customized book list · 2012-04-27 · quantum physics; probability theory and stochas-tic...

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J. Abonyi, Pannon University, Hungary; B. Feil, Pannon University,

Hungary

Cluster Analysis for Data Mining

and System Identification

This book presents new approaches to data miningand system identification. Algorithmsthat can beused for the clustering of data have been overviewed.New techniques andtools are presented for the clus-tering, classification, regression and visualization of-complex datasets. Special attention is given to theanalysis of historical process data,tailored algorithmsare presented for the data driven modeling of dy-namical systems,determining the model order ofnonlinear input-output black box models, and the-segmentation of multivariate time-series. The mainmethods and techniques areillustrated through sev-eral simulated and real-world applications from datamining andprocess engineering practice. The booksis aimed primarily at practitioners, researches, andprofessionals in statistics,data mining, business intel-ligence, and systems engineering, but it is also acces-sible tograduate and undergraduate students in ap-plied mathematics, computer science, electricalandprocess engineering. Familiarity with [..]

Features

Detailed overview of the most powerful algortihmsand approaches for data mining and system identifi-cation is presented Extensive references give a goodoverview of the current state of the application ofcomputational intelligence in data mining and sys-tem identification, and suggest further reading foradditional research Numerous illustrations to facili-tate the understanding of ideas and methods [..]

Contents

Classical fuzzy cluster analysis.- Visualization of theclustering results.- Clustering for fuzzy model identi-fication.- Fuzzy clustering for system identification.-Fuzzy model based classifiers.- Segmentation of mul-tivariate time-series.

Fields of interest

Applications of Mathematics; Statistical Theory andMethods; Statistics and Computing/Statistics Pro-grams; Statistics for Business/Economics/Math-ematical Finance/Insurance; Statistics for Engi-neering, Physics, Computer Science, Chemistry &Geosciences; Statistics for Life Sciences, Medicine,Health Sciences

Target groups

Practitioners, researchers, and professionals in statis-tics, data mining, business intelligence, and systemsengineering; undergraduate and graduate studentsin applied mathematics, computer science, as well aselectrical and process enigneering

Type of publication

Monograph

Due June 2007

2007. XVIII, 303 p. 120 illus. Hardcover

99,00 €

ISBN 978-3-7643-7987-2

G. Adenier, Växjö University, Växjö, Sweden; A.Y. Khrennikov,

Växjö University, Växjö, Sweden; C.A. Fuchs, Bell Labs, Murray

Hill, NJ, USA (Eds.)

Foundations of Probability and

Physics 4

All papers have been peer reviewed. This was the4th conference arranged by ICMM on probabilisticfoundations of classical and quantum physics. Thefirst three conferences took place in 2000, 2002, and2004. Some closely related conferences are BohmianMechanics 2000 and Quantum Theory: Reconsidera-tion of Foundations 2001, 2003, and 2005. The mainaim of these conferences is to understand the rolethat probability plays in the foundations of physics,theoretical as well as experimental, classical as wellas quantum. In this conference, as well as during ourprevious conferences, we are glad to welcome a fruit-ful assembly of theoretical physicists, experimenters,mathematicians, and even philosophers interested inthe foundations of probability and physics. Amongimportant topics discussed during the conferencewere the probabilistic foundations of quantum me-chanics, as well as the foundations of probabilityitself, the formation theory, quantum computing,quantum cryptography, quantum [..]

Fields of interest

Quantum Physics; Probability Theory and Stochas-tic Processes; Probability and Statistics in ComputerScience

Target groups

Researchers and graduate students in the fields ofquantum physics, mathematical physics, and philos-ophy of science

Type of publication

Proceedings

Due March 2007

2007. XII, 464 p. (Mathematical and Statistical Phsyics, Vol. 889)

Hardcover

154,00 €

ISBN 978-0-7354-0391-8

R.J. Adler, Israel Institute of Technology, Haifa, Israel; J. Taylor,

Stanford University, CA, USA

Random Fields and Geometry

This monograph is devoted to a completely new ap-proach to geometric problems arising in the study ofrandom fields. The groundbreaking material in PartIII, for which the background is carefully preparedin Parts I and II, is of both theoretical and practicalimportance, and striking in the way in which prob-lems arising in geometry and probability are beauti-fully intertwined. The three parts to the monographare quite distinct. Part I presents a user-friendly yetcomprehensive background to the general theoryof Gaussian random fields, treating classical topicssuch as continuity and boundedness, entropy andmajorizing measures, Borell and Slepian inequali-ties. Part II gives a quick review of geometry, bothintegral and Riemannian, to provide the reader withthe material needed for Part III, and to give somenew results and new proofs of known results alongthe way. Topics such as Crofton formulae, curvaturemeasures for stratified manifolds, critical point theo-ry, and tube formulae are covered. [..]

Features

Recasts old topics in random fields by following acompletely new way of handling both geometry andprobability Significant exposition of the work of oth-ers in the field Excellent reference work as well as ex-cellent work for self study

Contents

Preface.- Part I. Gaussian Processes. Gaussian Fields.Gaussian Inequalities. Orthogonal Expansions. Ex-cursion Probabilities. Stationary Fields.- Parat II. Ge-ometry. Integral Geometry. Differential Geometry.Piecewise Smooth Manifolds. Critical Point Theory.Volume of Tubes.- Part III. The Geometry of Ran-dom Fields. Random Fields on Euclidean Spaces.Random Fields on Manifolds. Mean Intrinsic Vol-umes. Excursion Probabilities for Smooth Fields.Non-Gaussian Geometry.- References.- Index.

Fields of interest

Probability Theory and Stochastic Processes; Geom-etry; Statistics, general; Mathematical Methods inPhysics

Target groups

Graduate students in Pure/Applied Probability andStatistics, researchers in a broad area of Mathematics

Type of publication

Monograph

Due July 2007

2007. XVII, 448 p. 21 illus. (Springer Monographs in Mathematics)

Hardcover

54,95 €

ISBN 978-0-387-48112-8

2 Statistics springer.com/booksellers

J. Albert, Bowling Green State University, Bowling Green, OH,

USA

Bayesian Computation with R

There has been a dramatic growth in the develop-ment and application of Bayesian inferential meth-ods. Some of this growth is due to the availability ofpowerful simulation-based algorithms to summa-rize posterior distributions. There has been also agrowing interest in the use of the system R for statis-tical analyses. R's open source nature, free availabil-ity, and large number of contributor packages havemade R the software of choice for many statisticiansin education and industry. Bayesian Computationwith R introduces Bayesian modeling by the use ofcomputation using the R language. The early chap-ters present the basic tenets of Bayesian thinking byuse of familiar one and two-parameter inferentialproblems. Bayesian computational methods such asLaplace's method, rejection sampling, and the SIR al-gorithm are illustrated in the context of a random ef-fects model. The construction and implementationof Markov Chain Monte Carlo (MCMC) methods isintroduced. These simulation-based algorithms are[..]

Features

Introduces Bayesian modeling by use of computationusing the R language

Contents

An introduction to R.- Introduction to Bayesianthinking.- Single parameter models.- Multiparame-ter models.- Introduction to Bayesian computation.-Markov chain Monte Carlo methods.- Hierarchicalmodeling.- Model comparision.- Regression mod-els.- Gibbs sampling.- Using R to interface with Win-BUGS.

Fields of interest

Statistics and Computing/Statistics Programs; Sim-ulation and Modeling; Computational Mathematicsand Numerical Analysis; Visualization; Optimization

Target groups

Instructors, students, practitioners

Type of publication

Graduate/advanced undergraduate textbook

Due August 2007

2007. X, 267 p. (Use R) Softcover

39,95 €

ISBN 978-0-387-71384-7

E. Allen, Texas Tech University, TX, USA

Modeling with Itô Stochastic

Differential Equations

Dynamical systems with random influences occurthroughout the physical, biological, and social sci-ences. By carefully studying a randomly varying sys-tem over a small time interval, a discrete stochasticprocess model can be constructed. Next, letting thetime interval shrink to zero, an Ito stochastic differ-ential equation model for the dynamical system isobtained. This modeling procedure is thoroughly ex-plained and illustrated for randomly varying systemsin population biology, chemistry, physics, engineer-ing, and finance. Introductory chapters present thefundamental concepts of random variables, stochas-tic processes, stochastic integration, and stochasticdifferential equations. These concepts are explainedin a Hilbert space setting which unifies and simpli-fies the presentation. Computer programs, giventhroughout the text, are useful in solving represen-tative stochastic problems. Analytical and compu-tational exercises are provided in each chapter thatcomplement the material in the text. [..]

Features

A procedure is thoroughly explained for construct-ing realistic stochastic differential equation modelsMany stochastic differential equation models are de-veloped for randomly varying systems in biology,physics, and finance Random variables, stochasticprocesses, stochastic integration, and stochastic dif-ferential equations are explained in a Hilbert spacesetting which unifies and simplifies the [..]

Contents

From the contents Random Variables.- StochasticProcesses.- Stochastic Integration.- Stochastic Differ-ential Equations.- Modeling{5.3.3} Ion transport.-References.- Basic Notation.- Index.

Fields of interest

Applications of Mathematics; Probability Theory andStochastic Processes; Mathematical Modeling andIndustrial Mathematics; Computational Mathemat-ics and Numerical Analysis

Target groups

Applied mathematicians, Mathematical biologists,Numerical analysts, Financial mathematicians; Prob-abilists, Statisticians, Engineers

Type of publication

Monograph

Due March 2007

2007. XII, 228 p. (Mathematical Modelling: Theory and Applica-

tions, Vol. 22) Hardcover

69,95 €

ISBN 978-1-4020-5952-0

S. Asmussen, Aarhus University, Aarhus, Denmark; P.W. Glynn,

Stanford University, Stanford, CA, USA

Stochastic Simulation: Algorithms

and Analysis

Sampling-based computational methods havebecome a fundamental part of the numericaltoolset of practitioners and researchers acrossan enormous number of different applied do-mains and academic disciplines. This book pro-vides a broad treatment of such sampling-basedmethods , as well as accompanying mathe-matical analysis of the convergence properties ofthe methods discussed . The reach of theideas is illustrated by discussing a wide range ofapplications and the models that have found wideusage. Given the wide range of exam-ples, exercises and applications stu-dents, practitioners and researchers in prob-ability, statistics, operations research, eco-nomics, finance, engineering as well as biol-ogy and chemistry and physics will find the book ofvalue.

Features

First rigorous and comprehensive advanced book onstochastic simulation Large amount of exercises andillustrations included Top world wide experts in area

Contents

What this Book is about.- Part A: General Methodsand Algorithms.- Generating Random Objects.- Out-put Analysis.- Steady-State Simulation.- VarianceReduction Methods.- Rare Event Simulation.- Gra-dient Estimation.- Stochastic Optimization.- Part B:Algorithms for Special Models.- Numerical Integra-tion.- Stochastic Differential Equations.- GaussianProcesses.- Lévy Processes.- Markov Chain MonteCarlo Methods.- Selected Topics and Extended Ex-amples.- Appendix.- Bibliography.- Index.

Fields of interest

Probability Theory and Stochastic Processes; Statisti-cal Theory and Methods; Operation Research/Deci-sion Theory; Industrial and Production Engineering;Operations Research, Mathematical Programming;Quantitative Finance

Target groups

Graduate students, researchers

Type of publication

Professional book

Due August 2007

2007. XIV, 476 p. (Stochastic Modelling and Applied Probability,

Vol. 57) Hardcover

49,95 €

ISBN 978-0-387-30679-7


F.E. Benth, University of Oslo, Norway; G. Di Nunno, Universi-

ty of Oslo, Norway; T. Lindstrom, University of Oslo, Norway; B.

Øksendal, University of Oslo, Norway; T. Zhang, University of

Manchester, UK (Eds.)

Stochastic Analysis and

Applications

The Abel Symposium 2005

Kiyosi Ito, the founder of stochastic calculus, is oneof the few central figures of the twentieth centurymathematics who reshaped the mathematical world.Today stochastic calculus is a central research fieldwith applications in several other mathematical dis-ciplines, for example physics, engineering, biology,economics and finance. The Abel Symposium 2005was organized as a tribute to the work of Kiyosi Itoon the occasion of his 90th birthday. Distinguishedresearchers from all over the world were invitedto present the newest developments within the ex-citing and fast growing field of stochastic analysis.The present volume combines both papers fromthe invited speakers and contributions by the pre-senting lecturers. A special feature is the Memoirsthat Kiyoshi Ito wrote for this occasion. These arevaluable pages for both young and established re-searchers in the field.

Features

High-profile, high quality conference on stochastics

Fields of interest

Probability Theory and Stochastic Processes; Anal-ysis; Statistical Theory and Methods; QuantitativeFinance; Mathematical and Computational Physics;Appl.Mathematics/Computational Methods of Engi-neering

Target groups

Researchers, graduate students in mathematics,statistics and mathematical physics

Type of publication

Contributed volume

Due May 2007

2007. XI, 678 p. (Abel Symposia, Vol. 2) Hardcover

79,95 €

ISBN 978-3-540-70846-9

R. Bhattacharya, University of Arizona, Tucson, AZ, USA; E.C.

Waymire, Oregon State University, Corvallis, OR, USA

A Basic Course in Probability Theory

Introductory Probability is a pleasure to read andprovides a fine answer to the question: How do youconstruct Brownian motion from scratch, given thatyou are a competent analyst? There are at least twoways to develop probability theory. The more famil-iar path is to treat it as its own discipline, and workfrom intuitive examples such as coin flips and co-nundrums such as the Monty Hall problem. An al-ternative is to first develop measure theory and anal-ysis, and then add interpretation. Bhattacharya andWaymire take the second path. To illustrate the au-thors' frame of reference, consider the two defini-tions they give of conditional expectation. The firstis as a projection of L2 spaces. The authors rely onthe reader to be familiar with Hilbert space operatorsand at a glance, the connection to probability maynot be not apparent. Subsequently, there is a discuss-sion of Bayes's rule and other relevant probabilisticconcepts that lead to a definition of conditional ex-pectation as an adjustment of [..]

Features

Quicker paced introduction to the basics allows fora more in-depth treatment of such topics as conver-gence theory and Brownian motion Self-containedand suitable for students with varying levels of back-ground in analysis and measure theory Includes acomplete overview of basic measure theory and anal-ysis (with proofs) Written in a lively and engagingstyle Contains an extensive bibliography

Contents

Random Maps, Distribution, and Mathematical Ex-pectation.- Independence, Conditional Expecta-tion.- Martingales and Stopping Times.- ClassicalZero-One Laws, Laws of Large Numbers and LargeDeviations.- Weak Convergence of Probability Mea-sures.- Fourier Series, Fourier Transform, and Char-acteristic Functions.- Classical Central Limit The-orems.- Laplace Transforms and Tauberian Theo-rem.- Random Series of Independent Summands.-Kolmogorov's Extension Theorem and Browni-an Motion.- Brownian Motion: The LIL and SomeFine-Scale Properties.- Skorokhod Embedding andDonsker's Invariance [..]

Fields of interest

Probability Theory and Stochastic Processes; Mea-sure and Integration; Analysis

Target groups

Advanced undergrads and graduate students, ana-lysts

Type of publication


Due August 2007

2007. XII, 210 p. (Universitext) Softcover

39,95 €

ISBN 978-0-387-71938-2

Y.M.M. Bishop, Washington, DC, USA; S.E. Fienberg, Carnegie

Mellon University, Pittsburgh, PA, USA; P.W. Holland, Educational

Testing Service, Princeton, NJ, USA

Discrete Multivariate Analysis

The scientist searching for structure in large systemsof data finds inspiration in his own discipline, sup-port from modern computing, and guidance fromstatistical models. Because large sets of data are likelyto be complicated, and because so many approachessuggest themselves, a codification of techniques ofanalysis, regarded as attractive paths rather than asstraitjackets, offers the scientist valuable directionsto try. The literature on discrete multivariate analy-sis, although extensive, is widely scattered. This bookbrings that literature together in an organized way.

Features

Originally published in 1974, this is a reprint of aclassic, still-valuable text

Contents

Introduction.- Structural models for counted data.-Maximum likelihood estimates for complete tables.-Formal goodness of fit: Summary statistics and mod-el selection.- Maximum likelihood estimation for in-complete tables.- Estimating the size of a closed pop-ulation.- Models for measuring change.- Analysis ofsquare tables: Symmetry and marginal homogene-ity.- Model selection and assessing closeness of fit:Practical aspects.- Other methods for estimation andtesting in cross-classifications.- Measures of associa-tion and agreement.- Pseudo-Bayes estimates of cellprobabilites.- Sampling [..]

Fields of interest

Statistical Theory and Methods

Target groups

Researchers, students

Type of publication

Monograph

Due July 2007

2007. X, 558 p. Softcover

49,95 €

ISBN 978-0-387-72805-6


P. Brito, University of Porto, Portugal; P. Bertrand, ENST Bretagne,

Cesson-Sévigné, France; G. Cucumel, ESG UQAM, Montréal, QC,

Canada; F. De Carvalho, Federal University of Pernambuco, Brazil

(Eds.)

Selected Contributions in Data

Analysis and Classification

This volume presents recent methodological devel-opments in data analysis and classification. A widerange of topics is covered that includes methods forclassification and clustering, dissimilarity analysis,graph analysis, consensus methods, conceptual anal-ysis of data, analysis of symbolic data, statistical mul-tivariate methods, data mining and knowledge dis-covery in databases. Besides structural and theoreti-cal results, the book presents a wide variety of appli-cations, in fields such as biology, micro-array analy-sis, cyber traffic, bank fraud detection, and text anal-ysis. Combining new methodological advances witha wide variety of real applications, this volume is cer-tainly of special value for researchers and practition-ers, providing new analytical tools that are useful intheoretical research and daily practice in classifica-tion and data analysis.

Contents

Analysis of Symbolic Data.- Clustering Methods.-Conceptual Analysis of Data.- Consensus Methods.-Data Analysis, Data Mining, and KDD.- Dissimilari-ties: Structures and Indices.- Multivariate Statistics.

Fields of interest

Statistical Theory and Methods; Data Mining andKnowledge Discovery; Pattern Recognition

Target groups

Researchers in statistics and data analysis

Type of publication

Monograph

Due August 2007

2007. XIII, 634 p. 131 illus. (Studies in Classification, Data Analy-

sis, and Knowledge Organization) Softcover

119,95 €

ISBN 978-3-540-73558-8

E.d. Castillo, The Pennsylvania State University, PA, USA

Process Optimization

A Statistical Approach

PROCESS OPTIMIZATION: A Statistical Approachis a textbook for a course in experimental optimiza-tion techniques for industrial production processesand other "noisy" systems where the main emphasisis process optimization. The book can also be usedas a reference text by Industrial, Quality and ProcessEngineers and Applied Statisticians working in in-dustry, in particular, in semiconductor/electronicsmanufacturing and in biotech manufacturing indus-tries.

Features

A much stronger treatment of the topic than the Wi-ley books published in this area for these reasons: (1)on the strength of the book’s author and (2) on itscoverage and treatment of process optimization Pro-vides in the form of a text a contemporary accountnot only of the classical techniques and tools used inDesign of Experiments (DOE) and Response SurfaceMethods (RSM), but also to present more advanced[..]

Contents

Preface.- An overview of empirical process optimiza-tion.- Optimization based on 1st order polynomialmodels.- Experimental designs for 1st order mod-els.- Analysis and optimization of 2nd order models.-Designs for 2nd order models.- Statistical inferencein 1st order RSM.- Statistical inference in 2nd orderRSM.- The bias vs. variance debate.- Robust param-eter design.- Robust optimization.- Introduction toBayesian inference.- Bayesian methods process op-timization.- Simulation optimization.- Kriging andcomputer experiments.- Appendices.- References.-Index.

Fields of interest

Industrial and Production Engineering; Probabili-ty Theory and Stochastic Processes; Optimization;Quality Control, Reliability, Safety and Risk; Engi-neering Design; Mathematical Modeling and Indus-trial Mathematics

Target groups

Professors and graduate students in Industrial Engi-neering and Statistics

Type of publication


Due August 2007

2007. XVIII, 476 p. 76 illus. (International Series in Operations Re-

search & Management Science, Vol. 105) Hardcover

79,95 €

ISBN 978-0-387-71434-9

É. Charpentier, Université Bordeaux 1, Talence, France; A. Lesne,

Université Pierre et Marie Curie, Paris, France; N.K. Nikolski, Uni-

versité Bordeaux 1, Talence, France (Eds.)

Kolmogorov's Heritage in

Mathematics

A.N. Kolmogorov (Tambov 1903, Moscow 1987)was one of the most brilliant mathematicians thatthe world has ever known. Incredibly deep and cre-ative, he was able to approach each subject with acompletely new point of view: in a few magnificentpages, which are models of shrewdness and imagina-tion, and which astounded his contemporaries, hechanged drastically the landscape of the subject. Eachchapter treats one of Kolmogorov's research themes,or a subject that was invented as a consequence ofhis discoveries. The authors present here his con-tributions, his methods, the perspectives he openedto us, the way in which this research has evolved upto now, along with examples of recent applicationsand a presentation of the modern prospects. Thisbook can be read by anyone with a master's (or evena bachelor's) degree in mathematics, computer sci-ence or physics, or more generally by anyone wholikes mathematical ideas. Rather than presenting de-tailed proofs, the main ideas are described, and a [..]

Features

Several world experts present one part of the math-ematical heritage left to us by Kolmogorov Ratherthan present detailed proofs, the main ideas are de-scribed.

Contents

Introduction: E. Charpentier, A. Lesne, N. Nikols-ki .- The youth of Andrei Nikolaevich and Fourierseries: J.-P. Kahane .- Kolmogorov's contributionto intuitionistic logic: T. Coquand.- Some aspectsof the probabilistic work: L. Chaumont, L. Mazli-ak, M. Yor.- Infinite dimensional Kolmogorov equa-tions: G. Da Prato.- From Kolmogorov's theorem onempirical distribution to number theory: K. Ford.-Kolmogorov's -entropy and the problem of statisti-cal estimation: M. Nikouline, V. Solev.- Kolmogorovand topology: V. M. Buchstaber .- Geometry and ap-proximation theory in A. N. Kolmogorov's [..]

Fields of interest

Mathematical Logic and Foundations; ProbabilityTheory and Stochastic Processes; Dynamical Systemsand Ergodic Theory; Fourier Analysis; Topology

Target groups

Mathematicians, physicists, computer scientists

Type of publication

Collection of essays

Due August 2007

Original French edition published by Éditions Belin, 2004

2007. VIII, 317 p. 22 illus. Hardcover

39,95 €

ISBN 978-3-540-36349-1


R.G. Cowell, Cass Business School, London, UK; A.P. Dawid, Uni-

versity of Cambridge, UK; S.L. Lauritzen, University of Oxford, UK;

D.J. Spiegelhalter, University of Cambridge, UK

Probabilistic Networks and Expert

Systems

Exact Computational Methods for Bayesian Networks

Winner of the 2002 DeGroot Prize. Probabilistic ex-pert systems are graphical networks that supportthe modelling of uncertainty and decisions in largecomplex domains, while retaining ease of calcula-tion. Building on original research by the authorsover a number of years, this book gives a thoroughand rigorous mathematical treatment of the under-lying ideas, structures, and algorithms, emphasizingthose cases in which exact answers are obtainable.It covers both the updating of probabilistic uncer-tainty in the light of new evidence, and statistical in-ference, about unknown probabilities or unknownmodel structure, in the light of new data. The carefulattention to detail will make this work an importantreference source for all those involved in the theoryand applications of probabilistic expert systems. Thisbook was awarded the first DeGroot Prize by the In-ternational Society for Bayesian Analysis for a bookmaking an important, timely, thorough, and notablyoriginal contribution to the [..]

Features

New in paperback Winner of the DeGroot Prize2002, the only book prize in the field of statistics

Contents

Introduction.- Logic, Uncertainty, and Probability.-Building and Using Probabilistic Networks.- GraphTheory.- Markov Properties on Graphs.- DiscreteNetworks.- Gaussian and Mixed Discrete-GaussianNetworks.- Discrete Multistage Decision Networks.-Learning About Probabilities.- Checking ModelsAgainst Data.- Structural Learning.

Fields of interest

Statistical Theory and Methods; Statistics for Engi-neering, Physics, Computer Science, Chemistry &Geosciences; Probability Theory and Stochastic Pro-cesses; Artificial Intelligence (incl. Robotics)

Target groups

Researchers, graduate students

Type of publication

Monograph

Due August 2007

2007. XII, 321 p. (Information Science and Statistics) Softcover

39,95 €

ISBN 978-0-387-71823-1

R.-A. Dana, Université Paris IX (Dauphine), Paris, France; M. Jean-

blanc, Université d'Evry, France

Financial Markets in Continuous

Time

In modern financial practice, asset prices are mod-elled by means of stochastic processes, and contin-uous-time stochastic calculus thus plays a centralrole in financial modelling. This approach has itsroots in the foundational work of the Nobel laureatesBlack, Scholes and Merton. Asset prices are furtherassumed to be rationalizable, that is, determined byequality of demand and supply on some market. Thisapproach has its roots in the foundational work onGeneral Equilibrium of the Nobel laureates Arrowand Debreu and in the work of McKenzie. This bookhas four parts. The first brings together a number ofresults from discrete-time models. The second devel-ops stochastic continuous-time models for the val-uation of financial assets (the Black-Scholes formu-la and its extensions), for optimal portfolio and con-sumption choice, and for obtaining the yield curveand pricing interest rate products. The third part re-calls some concepts and results of general equilibri-um theory, and applies this in [..]

Features

Explains key financial concepts, mathematical toolsand theories of mathematical finance Range of topicscovered is very broad for an introductory text Con-tains two separate appendices on Brownian motionand on numerical methods

Contents

The Discrete Case.- Dynamic Models in DiscreteTime.- The Black-Scholes Formula.- Portfolios Op-timizing Wealth and Consumption.- The YieldCurve.- Equilibrium of Financial Markets in DiscreteTime.- Equilibrium of Financial Markets in Continu-ous Time. The Complete Markets Case.- IncompleteMarkets.- Exotic Options.- Appendix A: BrownianMotion.- Appendix B: Numerical Methods.

Fields of interest

Quantitative Finance; Probability Theory andStochastic Processes

Target groups

Graduate students, undergraduate students and re-searchers

Type of publication


Due July 2007

Original French edition published by Economica, Paris, 1998

2007. XI, 326 p. (Springer Finance) Softcover

39,95 €

ISBN 978-3-540-71149-0

J. Dedecker, Unversité Paris 6, France; P. Doukhan, Unversité

Paris 1, France; G. Lang, Agro Paris Tech, Paris, France; J.R. Leon

R., Universidad Central de Venezuela, Caracas, Venezuela; S.

Louhichi, Université Paris-Sud, Orsay, France; C. Prieur, INSA

Toulouse, France

Weak Dependence: With Examples

and Applications

This monograph is aimed at developing Doukhan/Louhichi's (1999) idea to measure asymptotic inde-pendence of a random process. The authors proposevarious examples of models fitting such conditionssuch as stable Markov chains, dynamical systems ormore complicated models, nonlinear, non-Marko-vian, and heteroskedastic models with infinite mem-ory. Most of the commonly used stationary mod-els fit their conditions. The simplicity of the condi-tions is also their strength. The main existing toolsfor an asymptotic theory are developed under weakdependence. They apply the theory to nonparamet-ric statistics, spectral analysis, econometrics, and re-sampling. The level of generality makes those tech-niques quite robust with respect to the model. Thelimit theorems are sometimes sharp and always sim-ple to apply. The theory (with proofs) is developedand the authors propose to fix the notation for futureapplications. A large number of research papers dealswith the present ideas; the authors as well as numer-ous [..]

Features

Make it simple to read and thus the mathematicallevel needed is as low as possible Aimed to fix thenotions in the area in development May be consid-ered as an introduction to weak dependence Proposemodels and tools for practitioners hence the sectionsdevoted to examples are really extensive Some of thealready developed applications are also quoted forcompleteness

Contents

Introduction.- Weak dependence.- Models.- Toolsfor non causal cases.- Tools for causal cases.- Appli-cations of SLLN.- Central limit theorem.- Donskerprinciples.- Law of the iterated logarithm (LIL).- Theempirical process.- Functional estimation.- Spectralestimation.- Econometrics and resampling.

Fields of interest


Target groups

Practitioners, grad students

Type of publication

Monograph

Due August 2007

2007. XIV, 318 p. (Lecture Notes in Statistics, Vol. 190) Softcover

46,95 €

ISBN 978-0-387-69951-6


P.J. Diggle, University of Lancaster, UK; P.J. Ribeiro, Universidade

Federal do Paraná, Curitiba, Brazil

Model-based Geostatistics

Geostatistics is concerned with estimation and pre-diction problems for spatially continuous phenom-ena, using data obtained at a limited number of spa-tial locations. The name reflects its origins in mineralexploration, but the methods are now used in a widerange of settings including public health and thephysical and environmental sciences. Model-basedgeostatistics refers to the application of general sta-tistical principles of modeling and inference to geo-statistical problems. This volume is the first book-length treatment of model-based geostatistics. Theauthors have written an expository text, emphasizingstatistical methods and applications rather than theunderlying mathematical theory. Analyses of datasetsfrom a range of scientific contexts feature promi-nently, and simulations are used to illustrate theoret-ical results. Readers can reproduce most of the com-putational results in the book by using the authors'R-based software package, geoR, whose usage is illus-trated in a computation [..]

Features

The first book-length treatment of model-based geo-statistics

Contents

Introduction.- An Overview of Model-Based Geo-statistics.- Gaussian Models for Geostatistical Data.-Generalized Linear Models for Geostatistical Data.-Classical Parameter Estimation.- Spatial Prediction.-Bayesian Inference.- Geostatistical Design.

Fields of interest

Math. Applications in Geosciences; Statistical Theo-ry and Methods; Statistics for Engineering, Physics,Computer Science, Chemistry & Geosciences

Target groups


Type of publication

Monograph

Due March 2007

2007. XIII, 228 p. (Springer Series in Statistics) Hardcover

64,95 €

ISBN 978-0-387-32907-9

C. Donati-Martin, Université Pierre et Marie Curie, Paris, France;

M. Émery, Université Louis Pasteur, Strasbourg I, France; A.

Rouault, Université Versailles-Saint-Quentin, Versailles, France; C.

Stricker, Université des Besançon, France (Eds.)

Séminaire de Probabilités XL

Two noteworthy features of the 40th volume ofSéminaire de Probabilités are L. Coutin’s advancedcourse on calculus driven by fractional Brownianmotion, and a series of seven interrelated works onlocal time-space calculus. Other topics from stochas-tic processes and stochastic finance include threecontributions by A.S. Cherny on general approachesto arbitrage pricing.

Fields of interest

Probability Theory and Stochastic Processes; GameTheory, Economics, Social and Behav. Sciences

Target groups

Researchers and graduate students in probabilitytheory and stochastic processes

Type of publication

Contributed volume

Due July 2007

2007. XI, 481 p. (Séminaire de Probabilités, Vol. 1899) Softcover

59,95 €

ISBN 978-3-540-71188-9

R.A. Doney, University of Manchester, UK; J. Picard, Université

Blaise-Pascale Clermont-Ferrand, Aubière, France (Ed.)

Fluctuation Theory for Lévy

Processes

Ecole d'Eté de Probabilités de Saint-Flour XXXV - 2005

Lévy processes, i.e. processes in continuous timewith stationary and independent increments, arenamed after Paul Lévy, who made the connectionwith infinitely divisible distributions and describedtheir structure. They form a flexible class ofmodels, which have been applied to the study of stor-age processes, insurance risk, queues, turbulence,laser cooling, ... and of course finance, where thefeature that they include examples having "heavytails" is particularly important. Their sample path be-haviour poses a variety of difficult and fascinatingproblems. Such problems, and also some related dis-tributional problems, are addressed in detail in thesenotes that reflect the content of the course given byR. Doney in St. Flour in 2005.

Contents

1. Introduction to Lévy processes.- 2. Subordinators.-3. Local times and excursions.- 4. Ladder process-es and the Wiener-Hopf factorisation.- 5. FurtherWiener-Hopf developments.- 6. Creeping and relat-ed questions.- 7. Spitzer’s Condition.- 8. Lévy pro-cesses conditioned to stay positive.- 9. Spectrally neg-ative L´evy processes.- 10. Small-time behaviour.-References.- Index.

Fields of interest

Probability Theory and Stochastic Processes

Target groups

Researchers and graduate students

Type of publication

Monograph

Due April 2007

2007. IX, 147 p. (Ecole d'Eté Probabilit.Saint-Flour, Vol. 1897)

Softcover

29,95 €

ISBN 978-3-540-48510-0


N.J. Dorans, Educational Testing Service, Princeton, NJ, USA; M.

Pommerich, Monterey Bay Defense Manpower Data Center, Sea-

side, CA, USA; P.W. Holland, Educational Testing Service, Prince-

ton, NJ, USA (Eds.)

Linking and Aligning Scores and

Scales

The comparability of measurements made in dif-fering circumstances by different methods and in-vestigators is a fundamental pre-condition for allof science. Successful applications of technology re-quire comparable measurements. While the applica-tions herefocus on educational tests, score linkingissues are directly applicable to medicine and manybranches of behavioral science. Since the 1980s, thefields of educational and psychological measurementhave enhanced and widely applied techniques forproducing linked scores that are comparable. The in-terpretation attached to a linkage depends on howthe conditions of the linkage differ from the ideal.In this book, experts in statistics and psychometricsdescribe classes of linkages, the history of score link-ings, data collection designs, and methods used toachieve sound score linkages. They describe and crit-ically discuss applications to a variety of domains in-cluding equating of achievement exams, linkages be-tween computer-delivered exams and [..]

Features

Define what linking is, to distinguish among the va-rieties of linking and to describe different procedurefor linking Convey the complexity and diversity oflinking by covering different areas of linking andproviding diverse perspectives Written by experts inthe field of testing

Contents

Overview.- A framework and history for score link-ing.- Data collection designs and linking procedures,Michael J. Kolen.- Equating: best practices and chal-lenges to best practices, Nancy S. Petersen.- Practi-cal problems in equating test scores: a practioner'sperspective, Linda L. Cook.- Potential solutions topractical equating issues, Alina A. von Davier.- Scorelinking issues related to test content changes, JinghuaLiu and Michael E. Walker.- Linking scores derivedunder different modes of test administration, DanielR. Eignor.- Tests in transition: discussion and syn-thesis, Robert [..]

Fields of interest

Statistics for Social Science, Education, Public Policy,and Law; Assesment, Testing & Evaluation; Psycho-logical Methods/Evaluation; Psychometrics

Target groups

Researchers, practitioners

Type of publication

Monograph

Due July 2007

2007. XX, 396 p. (Statistics for Social and Behavioral Sciences)

Hardcover

54,95 €

ISBN 978-0-387-49770-9

M.A.R. Ferreira, University of Missouri, Columbia, MO, USA; H.K.H.

Lee, University of California, Santa Cruz, CA, USA

Multiscale Modeling

A Bayesian Perspective

A wide variety of processes occur on multiple scales,either naturally or as a consequence of measurement.This book contains methodology for the analysisof data that arise from such multiscale processes.The book brings together a number of recent devel-opments and makes them accessible to a wider au-dience. Taking a Bayesian approach allows for fullaccounting of uncertainty, and also addresses thedelicate issue of uncertainty at multiple scales. TheBayesian approach also facilitates the use of knowl-edge from prior experience or data, and these meth-ods can handle different amounts of prior knowledgeat different scales, as often occurs in practice.

Features

Stochastic models for processes that live and canpossibly be observed at different levels of resolutionThe models in this book allow different degrees ofsmoothness of the stochastic processes at the dif-ferent levels of resolution The statistical analysis ofmultiscale models based on the Bayesian paradigmin the book allow a full amount of uncertainty Con-tains implicit multiscale models implementable with[..]

Contents

Introduction.-Models for Spatial Data.-IllustrativeExample.-Convolution Methods.-Wavelet Meth-ods.-Overview on Explicit Multiscale Models.-Gaus-sian Multiscale Models on Trees.-Hidden MarkovModels on Trees.-Mass Balanced Multiscale Mod-els on Trees.-Multiscale Random Fields.-Multi-scale Time Series.-Change of Support Models.-Im-plicit Computationally-Linked Model Overview.-Metropolis-Coupled Methods.-Genetic Algo-rithms.-Soil Permeability Estimation.-Single PhotonEmission Computed Tomography Example.-Conclu-sions.

Fields of interest

Statistical Theory and Methods; Simulation andModeling; Image Processing and Computer Vision;Quantitative Geography; Econometrics

Target groups

Practitioners, researchers, graduate students

Type of publication

Monograph

Due August 2007

2007. XII, 245 p. (Springer Series in Statistics) Hardcover

62,95 €

ISBN 978-0-387-70897-3

S. Fienberg, Carnegie-Mellon University, Pittsburgh, PA, USA

The Analysis of Cross-Classified

Categorical Data

A variety of biological and social science data comein the form of cross-classified tables of counts, com-monly referred to as contingency tables. Until recentyears the statistical and computational techniquesavailable for the analysis of cross-classified data werequite limited. This book presents some of the recentwork on the statistical analysis of cross-classified da-ta using longlinear models, especially in the multidi-mensional situation.

Features

Originally published in 1980, this book has soldmore than 10,000 copies

Contents

Introduction.- Two-dimensional tables.- Three-di-mensional tables.- Selection of a model.- Four- andhigher-dimensional contingency tables.- Fixed mar-gins and logit models.- Causal analysis involving log-it and loglinear models.- Fixed and random zeroes.

Fields of interest


Target groups

Researchers, students

Type of publication

Monograph

Due July 2007

Originally published by Wiley-Interscience, 2002

2007. XIV, 202 p. Softcover

39,95 €

ISBN 978-0-387-72824-7


J.-P. Fouque, University of California, Santa Barbara, CA, USA; J.

Garnier, Université de Paris VII, Paris, France; G. Papanicolaou,

Stanford University, Stanford, CA, USA; K. Solna, University of Cal-

ifornia at Irvine, CA, USA

Wave Propagation and Time

Reversal in Randomly Layered

Media

Wave propagation in random media is an interdis-ciplinary field that has emerged from the need inphysics and engineering to model and analyze waveenergy transport in complex environments. Thisbook gives a systematic and self-contained presenta-tion of wave propagation in randomly layered mediausing the asymptotic theory of ordinary differentialequations with random coefficients. The first half ofthe book gives a detailed treatment of wave reflectionand transmission in one-dimensional random me-dia, after introducing gradually the tools from partialdifferential equations and probability theory that areneeded for the analysis. The second half of the bookpresents wave propagation in three-dimensional ran-domly layered media along with several applications,primarily involving time reversal. Many new resultsare presented here for the first time.

Features

Sections of notes where the authors give referencesand additional comments on the various results pre-sented are included at the end of each chapter

Contents

Introduction and Overview of the Book.- Waves inHomogeneous Media.- Waves in Random Media.-Waves in Layered Media.- Effective Properties ofRandomly Layered Media.- Scaling Limits.- Asymp-totics for Random Ordinary Differential Equations.-Transmission of Energy Through a Slab of Ran-dom Medium.- Wave-Front Propagation.- Statis-tics of Incoherent Waves.- Time Reversal in Reflec-tion and Spectral Estimation.- Applications to De-tection.- Time Reversal in Transmission.- Scatteringby a Three-Dimensional Randomly Layered Medi-um.- Time Reversal in a Three-Dimensional LayeredMedium.- [..]

Fields of interest

Applications of Mathematics; Probability Theoryand Stochastic Processes; Fluids; Partial DifferentialEquations; Acoustics; Appl.Mathematics/Computa-tional Methods of Engineering

Target groups

Graduate students and researchers

Type of publication

Monograph

Due August 2007

2007. XX, 612 p. (Stochastic Modelling and Applied Probability,

Vol. 56) Hardcover

54,95 €

ISBN 978-0-387-30890-6

R. Franklin, Virginia Commonwealth University, Richmond, VA,

USA; A. Mills, University of Virginia, Charlottesville, VA, USA (Eds.)

The Spatial Distribution of Microbes

in the Environment

Features

Attempts to address issues of scale of microbes jux-taposed with the footprint of their activities on thelandscape Includes discussion of fungi in soils andplanktonic microorganisms in water in an attempt toreconcile differences in scale of those organisms totheir activity footprint Provides a primer on quanti-tative methods used to evaluate scale issues and dis-tributions in an effort to allow readers to [..]

Contents

Contributing Authors. Preface. Acknowledgements.Introduction; Franklin, R.B., Mills, A.L. StatisticalAnalysis of Spatial Structure in Microbial Communi-ties; Franklin, R.B., Mills, A.L. Bacterial Interactionsat the Microscale - Linking Habitat to Function InSoil; Nunan N., Young, I.M, Crawford, J.W., Ritz,K. Spatial Distribution of Bacteria at the MicroscaleIn Soil; Dechesne, A., Pallud, C., Grundmann, G.L.Analysis Of Spatial Patterns Of Rhizoplane Colo-nization; Knudsen, G.R., Dandurand, L.-M. Micro-bial Distributions And Their Potential ControllingFactors In Terrestrial [..]

Fields of interest

Microbial Ecology; Statistics for Engineering,Physics, Computer Science, Chemistry & Geo-sciences; Biogeosciences

Target groups

Graduate students and scientists in the area of mi-crobial ecology, active investigators in general ecol-ogy who are interested in biogeochemical process-es, microbiologists who are just beginning to consid-er the environmental distribution of populations orcommunities of newly discovered organisms

Type of publication

Contributed volume

Due July 2007

2007. XII, 333 p. Hardcover

129,95 €

ISBN 978-1-4020-6215-5

B.D. Furberg, Kungsbacka, Sweden; C.D. Furberg, Wake Forest

University School of Medicine, Winston-Salem, NC, USA

Evaluating Clinical Research

All that glitters is not gold

The objective of this book is to make its readers bet-ter informed and more critical consumers of clinicalresearch to help them recognize the strengths andthe weaknesses of scientific publications. In doingso, the reader will be able to distinguish patient-im-portant and methodologically sound studies fromthose having limitations in design, conduct and in-terpretation. There are no prerequisites for readingthis book. The text is basic and has no statistical for-mulas. Key take-home messages are listed at the endof each chapter. The large number of cartoons hastwo purposes: First, to make the text easier to readand generate a few laughs and, second, to underscorespecific points, sometimes in a provocative way.

Features

Updates and expands the first edition of this text, re-leased in 1994 The previous edition was only avail-able in Swedish

Contents

What is the Purpose of This Book?.- Why is Bene-fit-to-Harm Balance Essential to Treatment Deci-sions?.- What are the Strengths of Randomized Con-trolled Clinical Trials?.- What are the Weaknesses ofRandomized Controlled Clinical Trials?.- Do Meta-Analyses Provide the Ultimate Truth?.- What are theStrengths of Observational Studies?.- What are theWeaknesses of Observational Studies?.- Were theScientific Questions Specified in Advance?.- Werethe Treatment Groups Comparable Initially?.- Whyis Blinding/Masking So Important?.- How is Symp-tomatic Improvement Measured?.- is it Really [..]

Fields of interest

Statistics for Life Sciences, Medicine, Health Sci-ences; Quality of Life Research; Pharmacology/Toxi-cology

Target groups

Clinicians, practitioners

Type of publication

Monograph

Due August 2007

2007. V, 165 p. Softcover

24,95 €

ISBN 978-0-387-72898-8


J.E. Gentle, George Mason University, Fairfax, VA, USA

Matrix Algebra

Theory, Computations, and Applications in Statistics

Matrix algebra is one of the most important areas ofmathematics for data analysis and for statistical the-ory. The first part of this book presents the relevantaspects of the theory of matrix algebra for applica-tions in statistics. This part begins with the funda-mental concepts of vectors and vector spaces, nextcovers the basic algebraic properties of matrices,then describes the analytic properties of vectors andmatrices in the multivariate calculus, and finally dis-cusses operations on matrices in solutions of linearsystems and in eigenanalysis. This part is essentiallyself-contained. The second part of the book beginswith a consideration of various types of matrices en-countered in statistics, such as projection matricesand positive definite matrices, and describes the spe-cial properties of those matrices. The second part al-so describes some of the many applications of matrixtheory in statistics, including linear models, multi-variate analysis, and stochastic processes. The briefcoverage [..]

Features

This book's emphasis is on the areas of matrix anal-ysis that are important for statisticians Addressescomputational issues, places more emphasis on ap-plications that existing texts and is written in an in-formal style

Contents

Basic Vector/Matrix Structure and Notation.-Vec-tors and Vector Spaces.- Basic Properties of Matri-ces.- Vector/Matrix Derivatives and Integrals.- Ma-trix Tranformations and Factorizations.- Solutionof Linear Systems.- Evaluation of Eigenvalues andEigenvectors.- Special Matrices and Operations Use-ful in Modeling and Data Analysis.- Selected Appli-cations in Statistics.- Numerical Methods.- Numeri-cal Linear Algebra.- Software for Numerical LinearAlgebra.

Fields of interest

Statistical Theory and Methods; Numeric Comput-ing; Probability and Statistics in Computer Science;Numerical and Computational Methods in Engi-neering; Computational Mathematics and NumericalAnalysis

Target groups

Students, researchers

Type of publication


Due August 2007

2007. XXII, 528 p. (Springer Texts in Statistics) Hardcover

69,95 €

ISBN 978-0-387-70872-0

I.I. Gikhman, A.V. Skorokhod

The Theory of Stochastic Processes

III

From the Reviews: "Gihman and Skorohod havedone an excellent job of presenting the theory in itspresent state of rich imperfection."D.W. Stroock inBulletin of the American Mathematical Society, 1980"To call this work encyclopedic would not give anaccurate picture of its content and style. Some partsread like a textbook, but others are more technicaland contain relatively new results. ... The expositionis robust and explicit, as one has come to expect ofthe Russian tradition of mathematical writing. Theset when completed will be an invaluable source ofinformation and reference in this ever-expandingfield."K.L. Chung in American Scientist, 1977 "Thedominant impression is of the authors' mastery oftheir material, and of their confident insight into itsunderlying structure."J.F.C. Kingman in Bulletin ofthe London Mathematical Society, 1977

Contents

Martingales and Stochastic Integrals.- Stochastic Dif-ferential Equations.- Stochastic Differential Equa-tions for Continuous Processes and ContinuousMarkov Processes in Rm.- Remarks.- Bibliography.-Appendix: Corrections to Volumes I and II.- SubjectIndex.

Fields of interest


Target groups

Researchers and graduate students in stochastic pro-cesses

Type of publication

Monograph

Due March 2007

Originally published as Vol. 232 in the series: Grundlehren der

mathematischen Wissenschaften

2007. IX, 387 p. (Classics in Mathematics) Softcover

39,95 €

ISBN 978-3-540-49940-4

A. Gustafsson, University of Karlstad, Sweden; A. Herrmann, Uni-

versity of St. Gallen, Switzerland; F. Huber, University of Mainz,

Germany (Eds.)

Conjoint Measurement

Methods and Applications

The book covers all recent developments in ConjointAnalysis. Leading scientists present theory and ap-plications of this technique. In short, the followingmodels, techniques, and applications are discussed:normative models that maximize return, extensionof choice-based conjoint simulations, latent class, hi-erarchical Bayes modelling, new choice simulators,normative models for representing competitive ac-tions and reactions (based on game theory), appli-cations in diverse areas, computation of monetaryequivalents of part worth, share/return optimisa-tion (including Pareto frontier analysis), coupling ofconjoint analysis with the perceptual and preferencemapping of choice simulator results.

Features

Latest developments in conjoint analysis which is themost important multivariate technique in marketingCovers all hot topics in the field

Contents

P.E. Green: Foreword.- Conjoint Analysis as an In-strument of Market Research Practice.- Measure-ment of Price Effects with Conjoint Analysis.- Mar-ket Simulation Using a Probabilistic Ideal VectorModel for Conjoint Data.- A Comparison of Con-joint Measurement with Self-Explicated Approach-es.- Non-geometric Plackett-Burman Designs inConjoint Analysis.- On the Influence of the Evalu-ation Methods in Conjoint Design.- EvolutionaryConjoint.- The Value of Extent-of-Preference Infor-mation in Choice-Based Conjoint Analysis.- A Mul-ti-trait Multi-method Validity Test of Partworth Es-timates.- [..]

Fields of interest

Marketing; Statistics for Business/Economics/Mathe-matical Finance/Insurance

Target groups

Researchers, graduate students, practitioners

Type of publication

Monograph

Due September 2007

2007. VII, 373 p. 39 illus. Hardcover

99,95 €

ISBN 978-3-540-71403-3


A. Handwerk, Hamburg, Germany; H. Willems, Amsterdam, The

Netherlands

Wolfgang Doeblin

A Mathematician Rediscovered

Wolfgang Doeblin, one of the great probabilists ofthe 20th century, was already widely known in the1950s for his fundamental contributions to the theo-ry of Markov chains. His coupling method becamea key tool in later developments at the interface ofprobability and statistical mechanics. But the fullmeasure of his mathematical stature became appar-ent only in 2000 when the sealed envelope contain-ing his construction of diffusion processes in termsof a time change of Brownian motion was finallyopened, 60 years after it was sent to the Academy ofSciences in Paris. The film of Agnes Handwerk andHarrie Willems documents scientific and human as-pects of this amazing discovery and throws new lighton the startling circumstances of his death at the ageof 25. I recommend it in the strongest terms. HansFöllmer, Faculty of Mathematics, Humboldt Univer-sity, Berlin

Features

Well-done documentary of the famous mathemati-cian Wolfgang Doeblin

Fields of interest

History of Mathematics; Probability Theory andStochastic Processes; Mathematical and Computa-tional Physics

Target groups

Mathematicians, physicists, teachers, historians, stu-dents, school students, science-interested laymen

Type of publication

Biography

Due May 2007

2007. DVD-Video PAL. (Springer VideoMATH)

39,95 €

ISBN 978-3-540-71959-5

A. Handwerk, Hamburg, Germany; H. Willems, Amsterdam, The

Netherlands

Wolfgang Doeblin

A mathematician rediscovered

Wolfgang Doeblin, one of the great probabilists ofthe 20th century, was already widely known in the1950s for his fundamental contributions to the theo-ry of Markov chains. His coupling method becamea key tool in later developments at the interface ofprobability and statistical mechanics. But the fullmeasure of his mathematical stature became appar-ent only in 2000 when the sealed envelope contain-ing his construction of diffusion processes in termsof a time change of Brownian motion was finallyopened, 60 years after it was sent to the Academy ofSciences in Paris. The film of Agnes Handwerk andHarrie Willems documents scientific and human as-pects of this amazing discovery and throws new lighton the startling circumstances of his death at the ageof 25. I recommend it in the strongest terms. HansFöllmer, Faculty of Mathematics, Humboldt Univer-sity, Berlin

Features

well-done documentary of the famous mathemati-cian Wolfgang Doeblin

Fields of interest

History of Mathematics; Probability Theory andStochastic Processes; Mathematical and Computa-tional Physics

Target groups

Mathematicians, physicists, teachers, historians, stu-dents, school students, science-interested laymen.

Type of publication

Biography

Due June 2007

2007. DVD-Video NTSC. (Springer VideoMATH)

39,95 €

ISBN 978-3-540-71960-1

Th.N. Herzog, U.S. Department of Housing and Urban Develop-

ment, Washington, DC, USA; F.J. Scheuren, Alexandria, VA, USA;

W.E. Winkler, U.S. Census Bureau, Washington, DC, USA

Data Quality and Record Linkage

Techniques

This book helps practitioners gain a deeper under-standing, at an applied level, of the issues involved inimproving data quality through editing, imputation,and record linkage. The first part of the book dealswith methods and models. Here, we focus on the Fel-legi-Holt edit-imputation model, the Little-Rubinmultiple-imputation scheme, and the Fellegi-Sunterrecord linkage model. Brief examples are includedto show how these techniques work. In the secondpart of the book, the authors present real-world casestudies in which one or more of these techniques areused. They cover a wide variety of application areas.These include mortgage guarantee insurance, medi-cal, biomedical, highway safety, and social insuranceas well as the construction of list frames and admin-istrative lists. Readers will find this book a mixtureof practical advice, mathematical rigor, managementinsight and philosophy. The long list of referencesat the end of the book enables readers to delve moredeeply into the subjects [..]

Features

There are no other books available addressing thissubject Readers will find this book a mixture of prac-tical advice, mathematical rigor, management insightand philosophy The authors also discuss the softwarethat has been developed to apply the techniques de-scribed in the text

Contents

Introduction.- What is Data Quality and WhyShould We Care?.- Examples of Companies UsingData to their Advantage/Disadvantage.- Propertiesof Data Quality and Metrics for Measuring it.- Ba-sic Data Quality Tools.- Mathematical Preliminariesfor Specialized Data Quality Techniques.- AutomaticEditing and Imputation of Survey Data--A UnifiedApproach to Identifying and Correcting Data Prob-lems in Sample Surveys.- Record Linkage--Method-ology.- Estimating the Parameters of Fellegi-SunterRecord Linkage Model.- Standardization and Pars-ing.- Phonetic Coding Systems for Names and/Or [..]

Fields of interest

Database Management; Statistical Theory and Meth-ods; Statistics for Social Science, Education, PublicPolicy, and Law

Target groups

Practitioners

Type of publication

Monograph

Due May 2007

2007. XIII, 227 p. Softcover

34,95 €

ISBN 978-0-387-69502-0


W. Härdle, Humboldt-Universität zu Berlin, Germany; Z. Hlávka,

Charles University in Prague, Czech Republic

Multivariate Statistics:

Exercises and Solutions

The authors present tools and concepts of multivari-ate data analysis by means of exercises and their so-lutions. The first part is devoted to graphical tech-niques. The second part deals with multivariate ran-dom variables and presents the derivation of estima-tors and tests for various practical situations. Thelast part introduces a wide variety of exercises in ap-plied multivariate data analysis. The book demon-strates the application of simple calculus and basicmultivariate methods in real life situations. It con-tains altogether 234 solved exercises which can as-sist a university teacher in setting up a modern mul-tivariate analysis course. All computer-based exer-cises are available in the R or XploRe languages. Thecorresponding libraries are downloadable from theSpringer link web pages and from the author’s homepages.

Features

Considers techniques like Conjoint MeasurementAnalyses, Applications to Finance, Projection Pur-suit and SIR techniques that are not found typicallyin multivariate textbooks Data sets discussed in thebook can be downloaded and analyzed by every sta-tistical package Online version powered by XploReallows immediate calculation of formulae

Contents

Comparison of Batches.- A Short Excursion IntoMatrix Algebra.- Moving to Higher Dimensions.-Multivariate Distributions.- Theory of The Multinor-mal.- Theory of Estimation.- Hypothesis Testing.-Decomposition of Data Matrices by Factors.- Princi-pal Components Analysis.- Factor Analysis.- ClusterAnalysis.- Discriminate Analysis.- CorrespondenceAnalysis.- Canonical Correlation Analysis.- Multi-dimensional Scaling.- Conjoint Measurement Anal-ysis.- Applications in Finance.- Highly Interactive,Computationally Intensive Techniques.

Fields of interest

Statistical Theory and Methods; ComputationalMathematics and Numerical Analysis; Visualization;Data Mining and Knowledge Discovery; Numericaland Computational Methods in Engineering

Target groups

Students in Economics and Finance

Type of publication


Due August 2007

2007. XIII, 368 p. Softcover

42,95 €

ISBN 978-0-387-70784-6

W. Härdle, Humboldt-Universität zu Berlin, Germany; L. Simar,

Université de Louvain-la-Neuve, Belgium

Applied Multivariate Statistical

Analysis

Most of the observable phenomena in the empiri-cal sciences are of a multivariate nature.In financialstudies, assets in stock markets are observed simul-taneously and their joint development is analyzedto better understand general tendencies and to trackindices. In medicine recorded observations of sub-jects in different locations are the basis of reliable di-agnoses and medication. In quantitative marketingconsumer preferences are collected in order to con-struct models of consumer behavior. The underlyingtheoretical structure of these and many other quanti-tative studies of applied sciences is multivariate. Fo-cussing on applications this book presents the toolsand concepts of multivariate data analysis in a waythat is understandable for non-mathematicians andpractitioners who face statistical data analysis. In thissecond edition a wider scope of methods and appli-cations of multivariate statistical analysis is intro-duced. All quantlets have been translated into the Rand Matlab language and [..]

Features

Wide scope of methods and applications Quantletsin R and Matlab available online Many examples andexercises

Contents

I Descriptive Techniques: Comparison of Batches.- IIMultivariate Random Variables: A Short Excursioninto Matrix Algebra; Moving to Higher Dimensions;Multivariate Distributions; Theory of the Multinor-mal; Theory of Estimation; Hypothesis Testing.- IIIMultivariate Techniques: Decomposition of DataMatrices by Factors; Principal Components Analy-sis; Factor Analysis; Cluster Analysis; DiscriminantAnalysis.- Correspondence Analysis.- CanonicalCorrelation Analysis.- Multidimensional Scaling.-Conjoint Measurement Analysis.- Application in Fi-nance.- Computationally Intensive Techniques.- [..]

Fields of interest

Statistical Theory and Methods; Economic Theory;Quantitative Finance; Statistics for Business/Eco-nomics/Mathematical Finance/Insurance

Target groups

Students in economics and finance

Type of publication


Due July 2007

2007. XII, 458 p. Softcover

69,95 €

ISBN 978-3-540-72243-4

J. Janssen, Solvay Business School, Brussels, Belgium; R. Manca,

Università di Roma "La Sapienza," Rome, Italy

Semi-Markov Risk Models for

Finance, Insurance and Reliability

This book presents applications of semi-Markov pro-cesses in finance, insurance and reliability, using re-al-life problems as examples. After a presentationof the main probabilistic tools necessary for under-standing of the book, the authors show how to ap-ply semi-Markov processes in finance, starting fromthe axiomatic definition and continuing eventuallyto the most advanced financial tools, particularly ininsurance and in risk-and-ruin theories. Also consid-ered are reliability problems that interact with creditrisk theory in finance. The unique approach of thisbook is to solve finance and insurance problems withsemi-Markov models in a complete way and further-more present real-life applications of semi-Markovprocesses.

Contents

Preface.- Probability Tools for Stochastic Model-ing.- Renewal Theory and Markov Chains.- MarkovRenewal Processes, Semi-Markov Processes andMarkov Random Walks.- Discrete Time and Re-ward SMP and Their Numerical Treatment.- Se-mi-Markov Extensions of the Black-Scholes Model.-Other Semi-Markov Models in Finance and Insur-ance.- Insurance Risk Models.- Reliability and CreditRisk Models.- Generalised Non-Homogeneous Mod-els for Pension Funds and Manpower Management.-References.- Author Index.- Subject Index.

Fields of interest

Probability Theory and Stochastic Processes; Quan-titative Finance; Finance /Banking; Financial Eco-nomics; Numerical Analysis

Target groups

Applied mathematicians, statisticians, financial in-termediaries, actuaries, engineers, operations re-searchers

Type of publication

Monograph

Due March 2007

2007. XVII, 429 p. Hardcover

62,95 €

ISBN 978-0-387-70729-7


J. Jiang, University of California, Davis, CA, USA

Linear and Generalized Linear

Mixed Models and Their

Applications

This book covers two major classes of mixed effectsmodels, linear mixed models and generalized linearmixed models, and it presents an up-to-date accountof theory and methods in analysis of these modelsas well as their applications in various fields. Thebook offers a systematic approach to inference aboutnon-Gaussian linear mixed models. Furthermore,it has included recently developed methods, such asmixed model diagnostics, mixed model selection,and jackknife method in the context of mixed mod-els. The book is aimed at students, researchers andother practitioners who are interested in using mixedmodels for statistical data analysis. The book is suit-able for a course in a M.S. program in statistics, pro-vided that the section of further results and techni-cal notes in each of the first four chapters is skipped.If these four sections are included, the book may beused for a course in a Ph. D. program in statistics. Afirst course in mathematical statistics, the ability touse computers for [..]

Features

Concentrates on two major classes of mixed effectsmodels, linear mixed models and generalized linearmixed models Offers an up-to-date account of theoryand methods in the analysis of these models as wellas their applications in various fields

Contents

Linear mixed models: Part I.- Linear mixed models:Part II.- Generalized linear mixed models: Part I.-Generalized linear mixed models: Part II.

Fields of interest

Statistical Theory and Methods; Health Care Admin-istration; Numerical Analysis; Genetics and Popula-tion Dynamics

Target groups

Researchers, graduate students, practitioners

Type of publication

Monograph

Due April 2007

2007. XIV, 257 p. (Springer Series in Statistics) Hardcover

69,95 €

ISBN 978-0-387-47941-5

G. Kirchgässner, University of St. Gallen, Switzerland; J. Wolters,

Freie Universität Berlin, Germany

Introduction to Modern Time Series

Analysis

This book presents modern developments in timeseries econometrics that are applied to macroeco-nomic and financial time series. It attempts to bridgethe gap between methods and realistic applications.This book contains the most important approach-es to analyse time series which may be stationary ornonstationary. Modelling and forecasting univariatetime series is the starting point. For multiple station-ary time series Granger causality tests and vector au-toregressive models are presented. For real appliedwork the modelling of nonstationary uni- or multi-variate time series is most important. Therefore, unitroot and cointegration analysis as well as vector er-ror correction models play a central part. Modellingvolatilities of financial time series with autoregressiveconditional heteroskedastic models is also treated.

Features

Presents recent and modern methods of time serieseconometrics Combines methods with real world ap-plications

Contents

Introduction and Basics.- Univariate Stationary Pro-cesses.- Granger Causality.- Vector AutoregressiveProcesses.- Nonstationary Processes.- Cointegra-tion.- Autoregressive Conditional Heteroskedastici-ty.

Fields of interest

Econometrics; Statistics for Business/Eco-nomics/Mathematical Finance/Insurance

Target groups

Students, researchers

Type of publication

Monograph

Due August 2007

2007. X, 274 p. 43 illus. Hardcover

79,95 €

ISBN 978-3-540-73290-7

K.-R. Koch, University of Bonn, Germany

Introduction to Bayesian Statistics

The Introduction to Bayesian Statistics (2nd edition)presents Bayes’ theorem, the estimation of unknownparameters, the determination of confidence regionsand the derivation of tests of hypotheses for the un-known parameters, in a manner that is simple, intu-itive and easy to comprehend. The methods are ap-plied to linear models, in models for a robust esti-mation, for prediction and filtering and in modelsfor estimating variance components and covariancecomponents. Regularization of inverse problems andpattern recognition are also covered while Bayesiannetworks serve for reaching decisions in systemswith uncertainties. If analytical solutions cannot bederived, numerical algorithms are presented, suchas the Monte Carlo integration and Markov ChainMonte Carlo methods.

Features

An easy to understand introduction to Bayesianstatistics Compares traditional and Bayesian meth-ods with the rules of probability presented in a logi-cal way allowing an intuitive understanding of ran-dom variables and their probability distributions tobe formed

Contents

1 Introduction.- 2 Probability.- 3 Parameter Estima-tion, Confidence Regions and Hypothesis Testing.- 4Linear Model.- 5 Special Models and Applications.- 6Numerical Methods.- References.- Index.

Fields of interest

Geophysics/Geodesy; Statistics for Engineering,Physics, Computer Science, Chemistry & Geo-sciences; Geoinformation/Cartography; Image Pro-cessing and Computer Vision

Target groups

Students and practitioners applying Bayes statisticsto geophysical and geodetic problems

Type of publication

Monograph

Due July 2007

2007. XII, 249 p. 17 illus. Hardcover

89,95 €

ISBN 978-3-540-72723-1


L. Koralov, University of Maryland, College Park, MD, USA; Y.G.

Sinai, Princeton University, NJ, USA

Theory of Probability and Random

Processes

A one-year course in probability theory and the the-ory of random processes, taught at Princeton Uni-versity to undergraduate and graduate students,forms the core of the content of this book It is struc-tured in two parts: the first part providing a detaileddiscussion of Lebesgue integration, Markov chains,random walks, laws of large numbers, limit theo-rems, and their relation to Renormalization Grouptheory. The second part includes the theory ofstationary random processes, martingales, general-ized random processes, Brownian motion, stochasticintegrals, and stochastic differential equations. Onesection is devoted to the theory of Gibbs randomfields. This material is essential to many undergrad-uate and graduate courses. The book can also serveas a reference for scientists using modern probabilitytheory in their research.

Features

Comprehensive, self-contained exposition of classi-cal probability theory and the theory of random pro-cesses Dwells on a number of modern topics, not ad-dressed in most textbooks Author Ya. G. Sinai is oneof the world's leading probabilists and mathematicalphysicists

Contents

From the Contents Part I Probability Theory: Spacesof Elementary Outcomes. Random Variables andtheir Distributions.- Sequences of Independent Tri-als. Lebesgue Integral and Mathematical Expecta-tion. Conditional Probabilities and Independence.-Markov Chains.- Random Walks on the Lattice Zd.-Laws of Large Numbers.- Weak Convergence ofMeasures.- Characteristic Functions.- Limit Theo-rems.- Several Interesting Problems. Part IIRandom Processes: Basic Concepts.- ConditionalExpectations and martingales.- Random Processeswhich are Stationary in the Wide Sense.- RandomProcesses [..]

Fields of interest


Target groups

Undergraduate and graduate students, lecturers inprobability theory and random processes

Type of publication


Due August 2007

Originally published as Springer Textbook: Probability Theory. An

Introductory Course

2007. XI, 353 p. (Universitext) Softcover

34,95 €

ISBN 978-3-540-25484-3

P. Lavallée, Statistics Canada, Ottawa, ON, Canada

Indirect Sampling

Following the classical sampling theory, the surveystatistician selects samples of people, businesses orothers, in order to obtain the desired information.Drawing the samples is usually done by randomly se-lecting from a list representing the target population.In practice, this list is often not available. At best, thestatistician only has access to a different list, indi-rectly related to the targeted population. The exam-ple of a survey of children where the statistician on-ly has a list of adult persons is a typical case. In thiscase, the statistician first draws a sample of adults,and for each selected adult, the statistician then iden-tifies his/her children. The survey is done from thelatter. This is what is called indirect sampling. Whenindirect sampling is used jointly with the samplingof clusters of persons (families, for example), manycomplications arise for the survey statistician. One ofthe complications relates to the computation of theestimates from the survey. The production [..]

Features

Parameters are estimated by not sampling the targetpopulation, but another population that is linked tothe target one The proposed approach offers elegantand practical solutions

Contents

Introduction.- Description and use of the GWSM.-Literature review.- Properties.- Other generalisa-tions.- Application to longitudinal surveys.- GWSMand calibration.- Non-response.- GWSM and recordlinkage.- Conclusion.

Fields of interest

Statistics for Social Science, Education, Public Policy,and Law; Statistical Theory and Methods; PopulationEconomics; Quality of Life Research; Demography;Methodology of the Social Sciences

Target groups

Statisticians

Type of publication

Monograph

Due May 2007

2007. XVI, 256 p. (Springer Series in Statistics) Hardcover

59,95 €

ISBN 978-0-387-70778-5

S.M. Lynch, Princeton University, Princeton, NJ, USA

Introduction to Applied Bayesian

Statistics and Estimation for Social

Scientists

"Introduction to Applied Bayesian Statistics and Es-timation for Social Scientists" covers the completeprocess of Bayesian statistical analysis in great detailfrom the development of a model through the pro-cess of making statistical inference. The key featureof this book is that it covers models that are mostcommonly used in social science research - includingthe linear regression model, generalized linear mod-els, hierarchical models, and multivariate regressionmodels - and it thoroughly develops each real-dataexample in painstaking detail. The first part of thebook provides a detailed introduction to mathemati-cal statistics and the Bayesian approach to statistics,as well as a thorough explanation of the rationale forusing simulation methods to construct summariesof posterior distributions. Markov chain Monte Car-lo (MCMC) methods - including the Gibbs samplerand the Metropolis-Hastings algorithm - are then in-troduced as general methods for simulating samplesfrom distributions. Extensive [..]

Features

First book written at an introductory level for socialscientists interested in learning about MCMC

Contents

Introduction.- Probability theory and classical statis-tics.- Basics of Bayesian statistics.- Modern model es-timation part 1: Gibbs sampling.- Modern model es-timation part 2: Metroplis-Hastings sampling.- Eval-uating MCMC algorithms and model fit.- The linearregression model.- Generalized linear models.- In-troduction to hierarchical models.- Introduction tomultivariate regression models.- Conclusion.

Fields of interest

Methodology of the Social Sciences; Statistics for So-cial Science, Education, Public Policy, and Law; De-mography

Target groups

Social scientists

Type of publication

Monograph

Due August 2007

2007. XXVIII, 357 p. (Statistics for Social and Behavioral Sciences)

Hardcover

59,95 €

ISBN 978-0-387-71264-2


T.J. Lyons, University of Oxford, UK; M. Caruana, University of Ox-

ford, UK; T. Lévy, École Normale Supérieure, Paris, France

Differential Equations Driven by

Rough Paths

Ecole d’Eté de Probabilités de Saint-Flour XXXIV-2004

Each year young mathematicians congregate in SaintFlour, France, and listen to extended lecture cours-es on new topics in Probability Theory. The goal ofthese notes, representing a course given by TerryLyons in 2004, is to provide a straightforward andself supporting but minimalist account of the key re-sults forming the foundation of the theory of roughpaths. The proofs are similar to those in the exist-ing literature, but have been refined with the benefitof hindsight. The theory of rough paths aims to cre-ate the appropriate mathematical framework for ex-pressing the relationships between evolving systems,by extending classical calculus to the natural modelsfor noisy evolving systems, which are often far fromdifferentiable.

Contents

A Word About the Summer School.- Foreword.-Introduction.- 1.Differential Equations Driven byModerately Irregular Signals.- 2.The Signature of aPath.- 3.Rough Paths.- 4.Integration along RoughPaths.- 5.Differential Equations Driven by RoughPaths.- References.- Index.

Fields of interest

Probability Theory and Stochastic Processes; Ordi-nary Differential Equations

Target groups

Researchers and graduate students

Type of publication

Monograph

Due May 2007

2007. XVIII, 109 p. 3 illus. (Ecole d'Eté Probabilit.Saint-Flour, Vol.

1908) Softcover

29,95 €

ISBN 978-3-540-71284-8

J. López-Fidalgo, Universidad de Castilla-La Mancha, Ciudad Real,

Spain; J.M. Rodríguez-Díaz, Universidad de Salamanca, Spain; B.

Torsney, University of Glasgow, UK (Eds.)

mODa 8 - Advances in Model-

Oriented Design and Analysis

Proceedings of the 8th International Workshop in Model-Ori-

ented Design and Analysis held in Almagro, Spain, June 4-8,

2007

The volume contains the proceedings of the 8thWorkshop on Model-Oriented Design and Analysis.This book offers leading and pioneering work on op-timal experimental designs, both from a mathemat-ical/statistical point of view and with regard to realapplications. Scientists from all over the world, fromEastern and Western Europe, the USA, Latin-Ameri-ca, Asia and Africa, have contributed to this volume.Primary topics are designs for nonlinear models andapplications to experimental medicine.

Features

Very latest results in optimal experimental designsContributors from all over the world

Fields of interest

Statistical Theory and Methods; Statistics for LifeSciences, Medicine, Health Sciences; Game The-ory/Mathematical Methods; Statistics for Busi-ness/Economics/Mathematical Finance/Insurance

Target groups

Scientists in the fields of statistics, especially medicalstatistics and optimization

Type of publication

Proceedings

Due May 2007

2007. XV, 241 p. 27 illus. (Contributions to Statistics) Softcover

64,95 €

ISBN 978-3-7908-1951-9

J.-M. Marin, Université Paris-Sud, Orsay, France; C.P. Robert, Uni-

versité Paris-Dauphine, Paris, France

Bayesian Core: A Practical Approach

to Computational Bayesian

Statistics

This Bayesian modeling book is intended for prac-titioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics.Focusing on standard statistical models and backedup by discussed real datasets available from the bookwebsite, it provides an operational methodology forconducting Bayesian inference, rather than focusingon its theoretical justifications. Special attention ispaid to the derivation of prior distributions in eachcase and specific reference solutions are given foreach of the models. Similarly, computational detailsare worked out to lead the reader towards an effec-tive programming of the methods given in the book.While R programs are provided on the book websiteand R hints are given in the computational sectionsof the book, The Bayesian Core requires no knowl-edge of the R language and it can be read and usedwith any other programming language. The BayesianCore can be used as a textbook at both undergradu-ate and graduate levels, as [..]

Features

The perfect entry for gaining a practical understand-ing of Bayesian methodology Guides the reader intothe practice of prior modeling and Bayesian comput-ing for the most classical models Computational as-pects are sufficiently detailed to achieve effective pro-gramming of the methods with little effort Datasets,R codes and course slides are available on the bookwebsite

Contents

User's manual.- Normal models.- Regression andvariable selection.- Generalised linear models.- Cap-ture-recapture experiments.- Mixture models.- Dy-namic models.- Image analysis.

Fields of interest

Statistical Theory and Methods; Probability andStatistics in Computer Science; Simulation and Mod-eling; Numerical and Computational Methods in En-gineering; Signal,Image and Speech Processing; En-vironmental Computing/Environmental Modelling

Target groups

Students

Type of publication


Due March 2007

2008. XIII, 255 p. (Springer Texts in Statistics) Hardcover

59,95 €

ISBN 978-0-387-38979-0


J.P. Marques de Sá, Universidade do Porto, Portugal

Applied Statistics Using SPSS,

STATISTICA, MATLAB and R

This practical reference provides a comprehensiveintroduction and tutorial on the main statisticalanalysis topics, demonstrating their solution withthe most common software package. Intended foranyone needing to apply statistical analysis to a largevariety of science and enigineering problems, thebook explains and shows how to use SPSS, MATLAB,STATISTICA and R for analysis such as data de-scription, statistical inference, classification and re-gression, factor analysis, survival data and direction-al statistics. It concisely explains key concepts andmethods, illustrated by practical examples using re-al data, and includes a CD-ROM with software toolsand data sets. Readers learn which software tools toapply and gain insights into the comparative capa-bilities of the primary software packages. Major im-provements of the second edition are the inclusionof the R language, a new section on bootstrap esti-mation methods and an improved treatment of treeclassifiers as well as extra examples and exercises.

Features

Wide coverage of Statistical topics and methods Ap-plication to real life data and problems in variousfields Guidance on how to use STATISTICA, SPSS,MATLAB and R in statistical analysis applicationsIncluding CD-ROM with datasets (sources: engi-neering, medicine, biology, geology) and tools

Contents

Introduction.- Presenting and Summarising the Da-ta.- Estimating Data Parameters.- Parametric Testsof Hypotheses.- Non-Parametric Tests of Hypothe-ses.- Statistical Classification.- Data Regression.- Da-ta Structure Analysis.- Survival Analysis .- Direction-al Data.- Appendix A - Short Survey on ProbabilityTheory.- Appendix B – Distributions.- Appendix C -Point Estimation.- Appendix D – Tables.- AppendixE – Datasets.- Appendix F – Tools.

Fields of interest

Statistics for Engineering, Physics, Computer Sci-ence, Chemistry & Geosciences; Numerical andComputational Methods in Engineering; Sys-tems and Information Theory in Engineering;Appl.Mathematics/Computational Methods of Engi-neering

Target groups

Large audience needing to apply statistical methodse.g. students and professionals

Type of publication

Professional book

Due June 2007

2007. XXIV, 505 p.With CD-ROM. Hardcover

59,95 €

ISBN 978-3-540-71971-7

A.W. Marshall, University of British Columbia, Vancouver, BC,

Canada; I. Olkin, Stanford University, Stanford, CA, USA

Life Distributions

Structure of Nonparametric, Semiparametric, and Parametric

Families

For over 200 years, practitioners have been develop-ing parametric families of probability distributionsfor data analysis. More recently, an active develop-ment of nonparametric and semiparametric familieshas occurred. This book includes an extensive dis-cussion of a wide variety of distribution families—nonparametric, semiparametric and parametric—some well known and some not. An all-encompass-ing view is taken for the purpose of identifying rela-tionships, origins and structures of the various fam-ilies. A unified methodological approach for the in-troduction of parameters into families is developed,and the properties that the parameters imbue a dis-tribution are clarified. These results provide essentialtools for intelligent choice of models for data analy-sis. Many of the results given are new and have notpreviously appeared in print. This book provides acomprehensive reference for anyone working withnonnegative data.

Features

Devoted to the study of univariate distributions ap-propriate for the analyses of data known to be non-negative Includes much material from reliability the-ory in engineering and survival analysis in medicine

Contents

Preliminaries.- Ordering distributions: Descriptivestatistics.- Mixtures .- Nonparametric families: den-sities and hazard rates.- Nonparametric families: ori-gins in reliability theory.- Nonparametric famlies:inequalities for moments and survival functions.-Semiparametric families.- Exponential distributions.-Parametric extensions of the exponential distribu-tion.- Gompertz and Gompertz-Makeham distribu-tions- Pareto and F distributions and their paramet-ric extensions.- Logarithmic distributions.- InverseGaussian distributions.- Distributions with boundedsupport.- Additional [..]

Fields of interest

Quality Control, Reliability, Safety and Risk; Statisti-cal Theory and Methods

Target groups


Type of publication

Monograph

Due August 2007

2007. XX, 782 p. 138 illus. (Springer Series in Statistics) Hardcover

69,95 €

ISBN 978-0-387-20333-1

P. Massart, Université de Paris-Sud, Orsay, France; J. Picard, Uni-

versité Blaise-Pascale Clermont-Ferrand, Aubière, France (Ed.)

Concentration Inequalities and

Model Selection

Ecole d'Eté de Probabilités de Saint-Flour XXXIII - 2003

Since the impressive works of Talagrand, concen-tration inequalities have been recognized as funda-mental tools in several domains such as geometryof Banach spaces or random combinatorics. Theyalso turn out to be essential tools to develop a non-asymptotic theory in statistics, exactly as the centrallimit theorem and large deviations are known to playa central part in the asymptotic theory. An overviewof a non-asymptotic theory for model selection isgiven here and some selected applications to vari-able selection, change points detection and statisticallearning are discussed. This volume reflects the con-tent of the course given by P. Massart in St. Flour in2003. It is mostly self-contained and accessibleto graduate students.

Contents

1. Introduction.- 2. Exponential and information in-equalities.- 3. Gaussian processes.- 4. Gaussian mod-el selection.- 5. Concentration inequalities.- 6. Maxi-mal inequalities.- 7. Density estimation via model se-lection.- 8. Statistical learning.- References.- Index.

Fields of interest

Probability Theory and Stochastic Processes; Statisti-cal Theory and Methods; Information and Commu-nication, Circuits

Target groups

Graduate students and researchers

Type of publication

Monograph

Due April 2007

2007. XIV, 337 p. (Ecole d'Eté Probabilit.Saint-Flour, Vol. 1896)

Softcover

49,95 €

ISBN 978-3-540-48497-4


P.W.J. Mielke, Colorado State University, Fort Collins, CO, USA; K.J.

Berry, Colorado State University, Fort Collins, CO, USA

Permutation Methods

A Distance Function Approach

Most commonly-used parametric and permuta-tion statistical tests, such as the matched-pairs t testand analysis of variance, are based on non-metricsquared distance functions that have very poor ro-bustness characteristics. This second edition placesincreased emphasis on the use of alternative permu-tation statistical tests based on metric Euclidean dis-tance functions that have excellent robustness char-acteristics. These alternative permutation techniquesprovide many powerful multivariate tests includ-ing multivariate multiple regression analyses. In ad-dition to permutation techniques described in thefirst edition, this second edition also contains vari-ous new permutation statistical methods and studiesthat include resampling multiple contingency tableanalyses, analysis concerns involving log-linear mod-els with small samples, an exact discrete analog ofFisher’s continuous method for combining P-valuesthat arise from small data sets, multiple dichotomousresponse analyses, problems regarding [..]

Features

Makes a variety of powerful data analytic tools eas-ily available to practitioners New material has beenadded to the second edition

Contents

Introduction.- Description of MRPP.- AdditionalMRPP applications.- Description of MRBP.- Regres-sion analysis, prediction, and agreement.- Good-ness-of-Fit tests.- Contingency tables.- Multisamplehomogeneity tests.- Selected permutation studies.

Fields of interest

Statistical Theory and Methods; Biometrics; DataMining and Knowledge Discovery; Psychometrics;Health Care Administration; Monitoring/Environ-mental Analysis/Environmental Ecotoxicology

Target groups


Type of publication

Monograph

Due September 2007

2007. XVIII, 446 p. (Springer Series in Statistics) Hardcover

69,95 €

ISBN 978-0-387-69811-3

B. Möller, Technische Universität Dresden, Germany; U. Reuter,

Technische Universität Dresden, Germany

Uncertainty Forecasting in

Engineering

This book deals with uncertainty forecasting basedon a fuzzy time series approach, including fuzzy ran-dom processes and artificial neural networks. A con-sideration of data and measurement uncertainty en-hances forecasting in a wide range of applications,particularly in the fields of engineering, environmen-tal science and civil engineering. Uncertain data aredescribed by means of a new incremental fuzzy rep-resentation which permits a complete and accurateestimation of uncertainty. The book is aimed at en-gineers as well as professionals working in relatedfields. Descriptive, modeling and forecasting meth-ods pertaining to fuzzy time series are introducedand explained in detail. Emphasis is placed on fore-casting with the aid of fuzzy random processes, suchas fuzzy ARMA processes and fuzzy white-noise pro-cesses, as well as forecasting based on artificial neuralnetworks. All numerical algorithms are comprehen-sively described and demonstrated by way of practi-cal examples.

Features

Fuzzy time series can be applied in many fields inengineering like environmental engineering or civilengineering Two simulation-based important fore-casting strategies are explained: forecasting based onfuzzy-ARMA-processes or fuzzy-white-noise-pro-cesses and forecasting based on fuzzy artificial neuralnetworks A complete new description of uncertaindata as incremental fuzzy data is given

Contents

Introduction.- Mathematical Description of Uncer-tain Data.- Analysis of Time Series Comprised ofUncertain Data.- Forecasting of Time Series withUncertain Data.- Uncertain Forecasting in Engineer-ing and Environmental Science.- References.- Index.

Fields of interest

Statistics for Engineering, Physics, Computer Sci-ence, Chemistry & Geosciences; Theoretical and Ap-plied Mechanics; Environmental Computing/En-vironmental Modelling; Building Construction,HVAC, Refrigeration; Probability Theory andStochastic Processes

Target groups

Engineers, civil engineers, environmental scientists

Type of publication

Monograph

Due August 2007

2007. XIII, 202 p. 101 illus. Hardcover

89,95 €

ISBN 978-3-540-37173-1

W.G. Müller, Johannes Kepler Universität Linz, Austria

Collecting Spatial Data

Optimum Design of Experiments for Random Fields

The book is concerned with the statistical theoryfor locating spatial sensors. It bridges the gap be-tween spatial statistics and optimum design theo-ry. After introductions to those two fields the topicsof exploratory designs and designs for spatial trendand variogram estimation are treated. Special atten-tion is devoted to describing new methodologies tocope with the problem of correlated observations.A great number of relevant references are collect-ed and put into a common perspective. The theo-retical investigations are accompanied by a practi-cal example, the redesign of an Upper-Austrian airpollution monitoring network. A reader should beable to find respective theory and recommendationson how to efficiently plan a specific purpose spatialmonitoring network. The third edition takes intoaccount the rapid development in the area ofspatial statistics by including new relevant researchand references. The revised edition contains addi-tional material on design for detecting spatial [..]

Features

Book bridges the gap between spatial statistics andoptimum design theory New edition includes newrelevant research and references

Contents

Introduction.- Fundamentals of Spatial Statistics.-Fundamentals of Experimental Design.- ExploratoryDesigns.- Designs for Spatial Trend Estimation.- De-sign and Dependence.- Multipurpose Designs.- Ap-pendix.

Fields of interest

Regional Science; Statistics for Engineering, Physics,Computer Science, Chemistry & Geosciences; Math.Appl. in Environmental Science; Math. Applica-tions in Geosciences; Statistics for Business/Eco-nomics/Mathematical Finance/Insurance

Target groups

Scientists in regional and spatial science; practition-ers in regional planning

Type of publication

Monograph

Due August 2007

Originally published in the series: Contributions to Statistics by

Physica-Verlag Heidelberg, Germany

2007. XII, 242 p. 37 illus. Hardcover

84,95 €

ISBN 978-3-540-31174-4


H. Pham, Rutgers the State University of New Jersey, Piscataway,

NJ, USA (Ed.)

Springer Handbook of Engineering

Statistics

In today’s global and highly competitive environ-ment, continuous improvement in the processes andproducts of any field of engineering is essential forsurvival. Many organisations have shown that thefirst step to continuous improvement is to integratethe widespread use of statistics and basic data analy-sis into the manufacturing development process aswell as into the day-to-day business decisions tak-en in regard to engineering processes. The SpringerHandbook of Engineering Statistics gathers togetherthe full range of statistical techniques required by en-gineers from all fields to gain sensible statistical feed-back on how their processes or products are func-tioning and to give them realistic predictions of howthese could be improved. Featuring: Contributionsfrom leading experts in statistics and their applica-tion to engineering from industrial control to aca-demic medicine and financial risk management giv-ing all-round authoritative coverage. Wide-rangingselection of statistical [..]

Contents

Part A: Fundamental Statistics and Its ApplicationsStatistical Reliability with Applications.-Weibull Dis-tributions and Their Applications.-Characteriza-tions of Probability Distributions.-Two-Dimension-al Failure Modelling.-Prediction Intervals for Re-liability Growth Models with Small Sample Sizes.-Promotional Warranty Policies: Analysis and Per-spectives.-Stationary Marked Point Processes.-Mod-eling and Analyzing Yield, Burn-in and Reliabilityfor Semiconductor Manufacturing: Overview.- PartB: Process Monitoring and Improvement StatisticalMethods for Quality and Productivity [..]

Fields of interest

Quality Control, Reliability, Safety and Risk; Statis-tics for Engineering, Physics, Computer Science,Chemistry & Geosciences; Industrial and ProductionEngineering; Business/Management Science, general;Process and Chemical Engineering

Type of publication

Handbook

Due July 2007

2006. eReference.

249,00 €

ISBN 978-1-84628-288-1

C. Prévôt, University of Bielefeld, Germany; M. Röckner, Universi-

ty of Bielefeld, Germany

A Concise Course on Stochastic

Partial Differential Equations

These lectures concentrate on (nonlinear) stochas-tic partial differential equations (SPDE) of evolution-ary type. All kinds of dynamics with stochastic influ-ence in nature or man-made complex systems can bemodelled by such equations. To keep the technicali-ties minimal we confine ourselves to the case wherethe noise term is given by a stochastic integral w.r.t.a cylindrical Wiener process.But all results can beeasily generalized to SPDE with more general noisessuch as, for instance, stochastic integral w.r.t. a con-tinuous local martingale. There are basically threeapproaches to analyze SPDE: the "martingale mea-sure approach", the "mild solution approach” and the"variational approach". The purpose of these notes isto give a concise and as self-contained as possible anintroduction to the "variational approach”. A largepart of necessary background material, such as defi-nitions and results from the theory of Hilbert spaces,are included in appendices.

Contents

Motivation, Aims and Examples.- Stochastic Inte-gral in Hilbert spaces.- Stochastic Differential Equa-tions in Finite Dimensions.- A Class of StochasticDifferential Equations in Banach Spaces.- Appen-dices: The Bochner Integral.- Nuclear and Hilbert-Schmidt Operators.- Pseudo Invers of Linear Oper-ators.- Some Tools from Real Martingale Theory.-Weak and Strong Solutions: the Yamada-WatanabeTheorem.- Strong, Mild and Weak Solutions.

Fields of interest

Partial Differential Equations; Probability Theoryand Stochastic Processes

Target groups

Researchers and graduate students in mathematics,physics and economics

Type of publication

Monograph

Due June 2007

2007. VI, 144 p. (Lecture Notes in Mathematics, Vol. 1905) Soft-

cover

29,95 €

ISBN 978-3-540-70780-6

R.-D. Reiss, University of Siegen, Germany; M. Thomas, University

of Siegen, Germany

Statistical Analysis of Extreme

Values

with Applications to Insurance, Finance, Hydrology and Other

Fields

The statistical analysis of extreme data is importantfor various disciplines, including hydrology, insur-ance, finance, engineering and environmental sci-ences. This book provides a self-contained introduc-tion to the parametric modeling, exploratory analysisand statistical interference for extreme values. Theentire text of this third edition has been thorough-ly updated and rearranged to meet the new require-ments. Additional sections and chapters, elaboratedon more than 100 pages, are particularly concernedwith topics like dependencies, the conditional anal-ysis and the multivariate modeling of extreme data.Parts I–III about the basic extreme value methodol-ogy remain unchanged to some larger extent, yet no-table are, e.g., the new sections about "An Overviewof Reduced-Bias Estimation" (co-authored by M.I.Gomes), "The Spectral Decomposition Methodolo-gy", and "About Tail Independence" (co-authored byM. Frick), and the new chapter about "Extreme Val-ue Statistics of Dependent Random Variables" [..]

Features

Includes the statistical MS Windows applicationAcademic Xtremes 4.1 and StatPascal on a CD With-in the applied parts of the book one will find newchapters about Environmental Sciences (co-authoredby R.W. Katz) and Conditional Approaches to Fi-nancial Data "The present book is a valuable contri-bution to the various theoretical and applied prob-lems in the area of extreme value theory...a pleasureto read." [..]

Contents

Preface.- I. Modeling and Data Analysis.- II. Statisti-cal Interference in Parametric Models.- III. Elementsof Multivariate Statistical Analysis.- IV. Topics inHydrology, Insurance and Finance.- V. Case Studiesin Extreme Value Analysis.- Index.- Bibliography.

Fields of interest

Probability Theory and Stochastic Processes; Statis-tical Theory and Methods; Statistics and Comput-ing/Statistics Programs; Statistics for Business/Eco-nomics/Mathematical Finance/Insurance

Target groups

Students, researchers and practitioners

Type of publication


Due June 2007

2007. XVII, 511 p. 130 illus. With CD-ROM. Softcover

59,90 €

ISBN 978-3-7643-7230-9


C.P. Robert, Université Paris Dauphine, Paris, France

The Bayesian Choice

From Decision-Theoretic Foundations to Computational Im-

plementation

This paperback edition, a reprint of the 2001 edition,is a graduate-level textbook that introduces Bayesianstatistics and decision theory. It covers both the basicideas of statistical theory, and also some of the moremodern and advanced topics of Bayesian statisticssuch as complete class theorems, the Stein effect,Bayesian model choice, hierarchical and empiricalBayes modeling, Monte Carlo integration includ-ing Gibbs sampling, and other MCMC techniques.It was awarded the 2004 DeGroot Prize by the In-ternational Society for Bayesian Analysis (ISBA) forsetting "a new standard for modern textbooks deal-ing with Bayesian methods, especially those usingMCMC techniques, and that it is a worthy succes-sor to DeGroot's and Berger's earlier texts". Reviewof the second edition: "The text reads fluently andbeautifully throughout, with light, good-humouredtouches that warm the reader without being intru-sive. There are many examples and exercises, someof which draw out the essence of work of other [..]

Features

New in paperback, winner of the 2004 DeGroot Prize

Contents

Decision-theoretic foundations of statistical infer-ence.- From prior information to prior distribu-tions.- Bayesian point estimation.- Tests and con-fidence regions.- Bayesian Calculations.- ModelChoice.- Admissibility and complete classes.- Invari-ance, Haar measures, and equivariant estimators.-Hierarchical and empirical Bayes extensions.- A de-fense of the Bayesian choice.

Fields of interest


Target groups


Type of publication


Due July 2007

2007. XXV, 577 p. (Springer Texts in Statistics) Softcover

39,95 €

ISBN 978-0-387-71598-8

G. Schay, University of Massachusetts, Boston, MA, USA

Introduction to Probability with

Statistical Applications

Introduction to Probability with Statistical Appli-cations targets non-mathematics students, under-graduates and graduates, who do not need an ex-haustive treatment of the subject. While the pre-sentation is rigorous and contains theorems andproofs, linear algebra is largely avoided and only aminimal amount of multivariable calculus is need-ed. Key features:Clear definitions, simplified nota-tion and techniques of statistical analysis, combinedwith well-chosen examples and exercises, motivatethe expositionTheory and applications carefully bal-ancedTopics include random phenomena -- discreteand continuous random variables -- expectationsand variance, and common probability distributionssuch as the binomial, Poisson, and normalCombi-natorial principles involve all four arithmetic opera-tions; emphasis on tree diagramsReferences to moreadvanced concepts throughout the book, but may besafely skipped, depending on the reader For studentsin a variety of disciplines, including computer sci-ence, [..]

Features

Theory and applications carefully balanced Presen-tation is rigorous and contains theorems and proofsLinear algebra is largely avoided Clear definitions,simplified notation and techniques of statistical anal-ysis Well-chosen examples and exercises

Contents

Preface.- The Algebra of Events.- CombinatorialProblems.- Probabilities.- Random Variables.- Ex-pectation, Variance, Moments.- Some Special Distri-butions.- The Elements of Mathematical Statistics.-Bibliography.- Index.

Fields of interest

Probability Theory and Stochastic Processes; Statis-tics for Engineering, Physics, Computer Science,Chemistry & Geosciences; Probability and Statisticsin Computer Science; Measure and Integration; Ap-plications of Mathematics

Target groups

Advanced undergraduate and graduate students inComputer Science, Engineering, Natural and SocialSciences

Type of publication


Due September 2007

2007. X, 318 p. 44 illus. Softcover

34,90 €

ISBN 978-0-8176-4497-0

A. Sevilla, Moravian College, Bethlehem, PA, USA; K. Somers,

Moravian College, Bethlehem, PA, USA

Quantitative Reasoning

Tools for Today's Informed Citizen

This text is unique in that it takes an activity-basedapproach and fully integrates the use of technology.The authors make technology an essential compo-nent of the course using the argument that signifi-cant and more realistic problems can be investigatedusing technology, and with technology, students canconcentrate on ideas rather than computational de-tails.

Features

The authors developed this course with a grant fromthe National Science Foundation Each topic containsa number of worked-out examples and concludeswith a set of explorations or short problems for stu-dents to investigate The authors provide Excel andcalculator instructions with each activity Nearly allof the examples, explorations, and activities use realdata from print and electronic sources

Contents

Numerical Reasoning: Organizing information pic-torially using charts and graphs.- Bivariate data.-Graphs of functions.- Multiple variable functions.-Proportional, linear, and piecewise linear functions.-Modeling with linear and exponential functions.-Logarithms and scientific notation.- Indexes and rat-ings.- Personal finances.- Introduction to problemsolving.- Logical Reasoning: Decision making.- In-ductive reasoning.-Deductive reasoning.- Apportion-ment.- More on problem solving.- Statistical Reason-ing: Averages and five-number summary.- Standarddeviation, z-score and normal [..]

Fields of interest

Mathematics, general; Statistics, general; Statistics forSocial Science, Education, Public Policy, and Law

Target groups

Mathematics professors teaching Quantitative Rea-soning, Statistics, Liberal Arts Math

Type of publication

Undergraduate textbook

Due August 2007

2007. XXVII, 626 p. 75 illus. in color. Softcover

62,95 €

ISBN 978-1-931914-90-1


P.X.-K. Song, University of Waterloo, ON, Canada

Correlated Data Analysis: Modeling,

Analytics, and Applications

This book presents some recent developments incorrelated data analysis. It utilizes the class of dis-persion models as marginal components in the for-mulation of joint models for correlated data. Thisenables the book to handle a broader range of datatypes than those analyzed by traditional generalizedlinear models. One example is correlated angulardata. This book provides a systematic treatment forthe topic of estimating functions. Under this frame-work, both generalized estimating equations (GEE)and quadratic inference functions (QIF) are stud-ied as special cases. In addition to marginal modelsand mixed-effects models, this book covers topics onjoint regression analysis based on Gaussian copulasand generalized state space models for longitudinaldata from long time series. Various real-world dataexamples, numerical illustrations and software usagetips are presented throughout the book. This bookhas evolved from lecture notes on longitudinal dataanalysis, and may be considered suitable [..]

Features

New topics are featured that have not been discussedin other books: a unified framework of model forclustered, longitudinal, or vector outcomes basedon dispersion models A rigorous presentation of thetheory of inference functions prior to the introduc-tion to the marginal models The means of quadraticinference function (QIF) The theory of vector gener-alized linear models...and more!

Contents

Introduction and examples.- Dispersion models.-Inference functions.- Modeling correlated data.-Marginal generalized linear models.- Vector gen-eralized linear models.- Mixed-effects models: like-lihood-based inference.- Mixed-effects models:Bayesian inference.- Linear predictors.- Generalizedstate space models.- Generalized state space modelsfor longitudinal binomial data.- Generalized statespace models for longitudinal count data.- Missingdata in longitudinal studies.

Fields of interest


Target groups

Grad students, researchers

Type of publication

Monograph

Due August 2007

2007. XV, 346 p. (Springer Series in Statistics) Hardcover

69,95 €

ISBN 978-0-387-71392-2

B. Thompson, University of Missouri-Columbia, Columbia, MO,

USA

The Nature of Statistical Evidence

The purpose of this book is to discuss whether statis-tical methods make sense. That is a fair question, atthe heart of the statistician-client relationship, butput so boldly it may arouse anger. The many booksentitled something like Foundations of Statisticsavoid controversy by merely describing the variousmethods without explaining why certain conclusionsmay be drawn from certain data. But we statisticiansneed a better answer then just shouting a little loud-er. To avoid a duel, we prejudge the issue and askthe narrower question: "In what sense do statisticalmethods provide scientific evidence?" The presentvolume begins the task of providing interpretationsand explanations of several theories of statistical evi-dence. It should be relevant to anyone interested inthe logic of experimental science. Have we achieveda true Foundation of Statistics? We have made thelink with one widely accepted view of science and wehave explained the senses in which Bayesian statisticsand p-values allow [..]

Features

This book has substantial implications for all users ofStatistical methods

Contents

Mathematics and its Applications.- The Evolutionof Natural Scientists and their Theories.- Law andLearning.- Introduction to Probability.- The FairBetting Utility Interpretation of Probability.- Atti-tudes toward Chance.- A Framework for Statistics.-A Critique of Bayesian Inference.- The Long RunConsequence of Behavior.- A Critique of P-Values.-The Nature of Statistical Evidence.- The Science ofStatistics.- Comparison of Evidential Theories.

Fields of interest


Target groups


Type of publication

Monograph

Due March 2007

2007. X, 152 p. (Lecture Notes in Statistics, Vol. 189) Softcover

39,95 €

ISBN 978-0-387-40050-1

K. Wolter, University of Chicago, IL, USA

Introduction to Variance Estimation

We live in the information age. Statistical surveys areused every day to determine or evaluate public policyand to make important business decisions. Correctmethods for computing the precision of the surveydata and for making inferences to the target popula-tion are absolutely essential to sound decision mak-ing. Now in its second edition, Introduction to Vari-ance Estimation has for more than twenty years pro-vided the definitive account of the theory and meth-ods for correct precision calculations and inference,including examples of modern, complex surveys inwhich the methods have been used successfully. Thebook provides instruction on the methods that arevital to data-driven decision making in business,government, and academe. It will appeal to surveystatisticians and other scientists engaged in the plan-ning and conduct of survey research, and to thoseanalyzing survey data and charged with extractingcompelling information from such data. It will ap-peal to graduate students and university [..]

Features

The book is organized in a way that emphasizes boththe theory and applications of the various varianceestimating techniques Now in its second edition, In-troduction to Variance Estimation has for more thantwenty years provided the definitive account of thetheory and methods for correct precision calcula-tions and inference, including examples of modern,complex surveys in which the methods have beenused [..]

Contents

Introduction.- The method of random groups.-Vari-ance estimation based on balanced half-samples.-The jackknife method.- The bootstrap method.- Tay-lor series methods.- Generalized variance functions.-Variance estimation for systematic sampling.-Sum-mary of methods for complex surveys.

Fields of interest

Statistical Theory and Methods; Statistics for SocialScience, Education, Public Policy, and Law; Mar-keting; Assesment, Testing & Evaluation; Monitor-ing/Environmental Analysis/Environmental Ecotoxi-cology; Demography

Target groups


Type of publication

Monograph

Due March 2007

2007. XIV, 447 p. (Statistics for Social and Behavioral Sciences)

Hardcover

64,95 €

ISBN 978-0-387-32917-8

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