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Contents

Introductory Probability and Statistics ....................3

Statistical Theory and Methods ..............................3

Computational Statistics ..........................................9

Statistical Learning & Data Mining........................12

Biostatistics ............................................................14

Statistics in Genetics, Bioinformatics and Computational Biology..........................................19

Statistics in Business, Finance & Economics ..........20

Statistics in Engineering and Physical Science ......21

Statistics for Social and Behavioral Sciences ..........22

Page 8Page 6

Page 9 Page 12

Page 16 Page 19

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3

Introductory Probability and Statistics Introductory Probability and Statistics

Statistical Theory and Methods

For more information and complete contents, visit www.crcpress.com

Coming Soon!

A Whistle-StopTour of StatisticsBrian EverittRetired from King's College London,UK

This book introduces basic proba-bility and statistics through bite-size coverage of key topics.Designed as a revision aid andstudy guide, it describes key concepts from probabilityand statistics in self-contained sections. It also makes anexcellent reference for non-statisticians who need aneasy-to-follow reference for basic statistical techniques.The text shows how statistics can be applied in the realworld with examples, diagrams, and graphs to illustrateconcepts.

Catalog no. K13590, December 2011, c. 248 pp.Soft Cover, ISBN: 978-1-4398-7748-7$39.95 / £25.99

Coming Soon!

Introduction toProbability withTexas HoldemExamplesFrederic Paik SchoenbergUniversity of California-Los Angeles,USA

Using problems and examples from Texas Holdem, this isan engaging textbook for an introductory course in prob-ability. It covers all of the fundamentals, including permu-tations and combinations, conditional probability, Bayes’rule, random variables, simulation, correlation, laws oflarge numbers, the central limit theorem, Brownianmotion, Markov chains, and more. R code is availableonline for implementing topics in computational probability.

Catalog no. K11367, December 2011, c. 192 pp.Soft Cover, ISBN: 978-1-4398-2768-0$69.95 / £38.99

Introduction tothe Theory ofStatisticalInferenceHannelore LieroUniversity of Potsdam, Germany

Silvelyn ZwanzigUppsala University, Sweden

Series: Chapman & Hall/CRC Textsin Statistical Science

Based on the authors’ lecture notes, this text presentsconcise yet complete coverage of statistical inference the-ory, focusing on the fundamental classical principles.Unlike related textbooks, it combines the theoretical basisof statistical inference with a useful applied toolbox thatincludes linear models. Suitable for a second semesterundergraduate course on statistical inference, the textoffers proofs to support the mathematics and does notrequire any use of measure theory. It illustrates core con-cepts using cartoons and provides solutions to all exam-ples and problems.

Catalog no. K12437, July 2011, 284 pp., Soft CoverISBN: 978-1-4398-5292-7, $69.95 / £29.99

StatisticalInferenceThe Minimum DistanceApproachAyanendranath Basu,Hiroyuki Shioya, andChanseok ParkThis book gives a comprehensiveaccount of density-based mini-mum distance methods and theiruse in statistical inference. It covers statistical distances,density-based minimum distance methods, discrete andcontinuous models, asymptotic distributions, robustness,computational issues, residual adjustment functions,graphical descriptions of robustness, penalized and com-bined distances, multisample methods, weighted likeli-hood, and multinomial goodness-of-fit tests. The bookalso introduces the minimum distance methodology ininterdisciplinary areas, such as neural networks and imageprocessing, as well as specialized models and problems,including regression, mixture models, survival andBayesian analysis, and more.

Catalog no. K10008, June 2011, 429 pp.ISBN: 978-1-4200-9965-2, $89.95 / £57.99Also available as an eBook






4 SAVE 20% when you order online and enter Promo Code 499HM


SimultaneousInference inRegressionWei LiuUniversity of Southampton, UK

Series: Chapman & Hall/CRCMonographs on Statistics & AppliedProbability

With examples and MATLAB® pro-grams, this book provides a thor-ough overview of the construction methods and applica-tions of simultaneous confidence bands for various infer-ential purposes. Most of the text covers normal-error lin-ear regression models, although the author also describesthe logistic regression model to show how simultaneousconfidence bands can be constructed and used for gen-eralized linear regression models. MATLAB programs and color figures are available fordownload on the author’s website

Catalog no. K11385, 2010, 292 pp.ISBN: 978-1-4398-2809-0, $89.95 / £57.99Also available as an eBook

SmoothingSplinesMethods andApplicationsYuedong WangUniversity of California, SantaBarbara, USA


With many real-world examples, this book shows how toapply the powerful methods of smoothing splines in prac-tice. It covers basic smoothing spline models as well asmore advanced models. The author makes the advancedsmoothing spline methodology based on reproducingkernel Hilbert space (RKHS) accessible to practitioners andstudents by keeping theory to a minimum. R is usedthroughout to implement the methods.

Catalog no. C7755, June 2011, 384 pp.ISBN: 978-1-4200-7755-1, $89.95 / £57.99Also available as an eBook

Gaussian ProcessRegressionAnalysis forFunctional DataJian Qing ShiUniversity of Newcastle upon Tyne,UK

Taeryon ChoiKorea University, Seoul, South Korea

This work presents nonparametric statistical methods forfunctional regression analysis, specifically the methodsbased on a Gaussian process prior in a functional space.The authors discuss functional data analysis, theoreticalaspects based on the asymptotic properties of Gaussianprocess regression models, and new methodologicaldevelopments for high dimensional data and variableselection. They also explore novel nonparametric statisti-cal methods for curve prediction, curve clustering, func-tional ANOVA, and functional regression analysis of batchdata, repeated curves, and non-Gaussian data. MATLAB® and C codes are available on the author’s web-site.

Catalog no. K11716, July 2011, 216 pp.ISBN: 978-1-4398-3773-3, $99.95 / £63.99Also available as an eBook

Coming Soon!

FlexibleImputation ofMissing DataStef Van BuurenTNO Quality of Life, Leiden, TheNetherlands

Series: Chapman & Hall/CRCInterdisciplinary Statistics

A practical guide for handling missing data, this book pro-vides a flexible and accessible framework for multipleimputation along with strategies for obtaining effectivesolutions to these problems. The text is supported bymany examples using real data taken from the author’svast research involving missing data. All of the analysescan be replicated in R using the dedicated package MICE,which was developed by the author. Topics coveredinclude multiple imputation, multivariate and univariatemissing data, as well as issues of measurement, selection,and longitudinal data.

Catalog no. K13103, February 2012, c. 280 pp.ISBN: 978-1-4398-6824-9, $89.95 / £57.99






5



RobustNonparametricStatisticalMethodsSecond EditionThomas P. HettmanspergerPennsylvania State University,University Park, USA

Joseph W. McKeanWestern Michigan University, Kalamazoo, USA

Series: Chapman & Hall/CRC Monographs on Statistics &Applied Probability

“… a fine capstone course in non-parametric statistics.”—MAA Reviews, June 2011

Presenting an extensive set of tools and methods for dataanalysis, this second edition includes more models andmethods and significantly extends the possible analysesbased on ranks. It contains a new section on rank proce-dures for nonlinear models, a new chapter on modelswith dependent error structure, and new material on thedevelopment of computationally efficient affine invari-ant/equivariant sign methods based on transform-retransform techniques in multivariate models. Theauthors illustrate the methods using many real-worldexamples and R.


Introduction toStatistical LimitTheoryAlan M. PolanskyNorthern Illinois University, Dekalb,USA

“This book is clearly aimed at thestudent learning the material.The prose is clear and graphs areused well to illustrate concepts.Students will really like the large number of worked con-crete examples. … Each chapter has exercises and Rprojects that would be very helpful to solidify the under-standing of the material in the chapter. These and theworked examples would make this an excellent choicefor the student attempting to learn the materialthrough self-study …”

—MAA Reviews, June 2011

Catalog no. C6604, January 2011, 645 pp., ISBN: 978-1-4200-7660-8, $89.95 / £57.99Also available as an eBook

Introduction toGeneral andGeneralizedLinear ModelsHenrik Madsen and Poul ThyregodTechnical University of Denmark,Lyngby


Providing a flexible framework for data analysis andmodel building, this text focuses on the statistical meth-ods and models that can help predict the expected valueof an outcome, dependent, or response variable. It offersa sound introduction to general and generalized linearmodels using the popular and powerful likelihood tech-niques. Numerous examples show how the problems aresolved with R.

Catalog no. C9155, 2010, 316 pp.ISBN: 978-1-4200-9155-7, $79.95 / £39.99Also available as an eBook

Coming Soon!

NonparametricStatistical TestsA ComputationalApproachMarkus NeuhauserKoblenz University of AppliedSciences, Remagen, Germany

This book provides a modern and accessible overview ofcomputationally-intensive nonparametric statistical meth-ods. Presenting up-to-date and detailed information, thetext focuses on the use of permutation and bootstrapmethods to assess the significance of a statistic in ahypothesis test. It includes numerous real examples toillustrate the methods, and SAS programs are usedthroughout to apply them. In addition, a significant por-tion of the book is devoted to (recent) nonparametrictests for the comparison of independent groups withpotentially unequal variances.

Catalog no. K13006, December 2011, c. 256 pp.ISBN: 978-1-4398-6703-7, $89.95 / £57.99








Handbook ofMarkov ChainMonte CarloEdited by

Steve Brooks, Andrew Gelman, Galin Jones, and Xiao-Li Meng

Series: Chapman & Hall/CRCHandbooks of Modern Statistical Methods

“The Handbook of Markov Chain Monte Carlobecomes the third volume in the attractive and usefulChapman & Hall/CRC Handbooks of Modern StatisticalMethods Series. The author list is world-class, develop-ing 24 chapters, half on the theory side, half on appli-cations. The handbook provides a state-of-the-art viewof a technology that has revolutionized contemporarymodel fitting. Researchers at all levels of familiarity withMCMC will find novel morsels of material to chew on.”

—Alan E. Gelfand, James B. Duke Professor of StatisticalScience, Duke University, Durham, North Carolina, USA

Catalog no. C7941, May 2011, 619 pp.ISBN: 978-1-4200-7941-8, $99.95 / £63.99Also available as an eBook

Handbook ofParametric andNonparametricStatisticalProceduresFifth EditionDavid J. SheskinWestern Connecticut StateUniversity, Danbury, USA

Unsurpassed in accessibility, practicality, and scope, thefifth edition of this classic handbook provides up-to-date,in-depth coverage of more than 160 statistical proceduresas well as both theoretical and practical statistical topics.Including two new chapters on statistical modeling, thisupdated fifth edition contains substantial new material onstatistical quality control, meta-analysis and time seriesanalysis. Each chapter presents at least one example ofhow to compute a statistical test and offers decision tablesto help determine the appropriate test.

Catalog no. K12706, April 2011, 1926 pp.ISBN: 978-1-4398-5801-1, $169.95 / £108.00Also available as an eBook

Handbook ofSpatial StatisticsEdited by

Alan E. Gelfand, Peter J. Diggle, Montserrat Fuentes andPeter Guttorp

Series: Chapman & Hall/CRCHandbooks of Modern StatisticalMethods

“It is a comprehensive piece of work that summarizescurrent state of the developments of the spatial statisticsin its multitude. The range of topics covered is impres-sive … useful and enlightening for a wide scope of read-ers — from beginners to rather specialized researchers… Anybody even mildly interested in the theory or appli-cations of various parts of spatial statistics should readit, or even better, to have it handy as an authoritativeand remarkably useful reference.”

—ISCB News, No. 51, June 2011


Handbook ofFitting StatisticalDistributionswith RZaven A. KarianDenison University, Granville, Ohio, USA

Edward J. DudewiczSyracuse University, New York, USA

Along with in-depth coverage of cutting-edge applica-tions and contributions from experts who offer deepinsight on a range of topics, this comprehensive andauthoritative handbook presents the latest and bestmethods, algorithms, and computations for fitting distri-butions to data. The book covers GLD methodology andfitting systems, real-world applications in agriculture, reli-ability estimation, hurricanes/typhoons/cyclones, hailstorms, water systems, insurance and inventory manage-ment, and materials science. The accompanying CD-ROM includes the R programs used for many of the com-putations.







7



OptimalExperimentalDesign with RDieter Rasch, Jurgen Pilz,Rob Verdooren, andAlbrecht GebhardtThis book introduces experi-menters to the philosophy ofexperimentation, and the need forgood design and data collectionfor experiments. It gives experimenters and statisticiansguidance on how to construct optimum experimentaldesigns and calculate the sample size needed using R pro-grams. The book contains many detailed real-worldexamples that show how the R programs should be used.The authors discuss variations of the regression model,including linear and nonlinear regression models. Theyalso provide a final chapter of theoretical details for inter-ested mathematical statisticians.

Catalog no. K10876, May 2011, 345 pp.ISBN: 978-1-4398-1697-4, $99.95 / £63.99Also available as an eBook

PracticalMultivariateAnalysisFifth EditionAbdelmonem AfifiUniversity of California, Los Angeles,USA

Susanne MayUniversity of Washington, Seattle,USA

Virginia A. ClarkConsultant, Sequim, Washington, USA

Taking into account novel multivariate analyses as well asnew options for many standard methods, this renamed,new edition shows readers how to perform multivariatestatistical analyses and understand the results. For each ofthe techniques presented, the authors use the mostrecent software versions available, including R, and dis-cuss the most modern ways of performing the analysis.Along with more problems and data sets, this fifth editionincludes a new chapter on regression of correlated out-comes. Data sets and code are available for downloadonline.


A Practitioner’sGuide toResampling forData Analysis,Data Mining, andModelingPhillip I. GoodConsultant, Huntington Beach,California, USA

This practical guide discusses the applications of theseresampling methods, focusing on the areas of microarraysand data mining. Each chapter contains a wealth of exer-cises along with R and Stata code. Written by a leadingauthority in the field, the text covers such topics as esti-mation, the bootstrap method, multivariate tests, deci-sion trees, categorical data, multiple hypotheses, andmodel building.

Catalog no. K12588, August 2011, 224 pp.ISBN: 978-1-4398-5550-8, $89.95 / £57.99

Bayesian Ideasand Data AnalysisAn Introduction forScientists andStatisticiansRonald Christensen,Wesley Johnson, Adam Branscum, andTimothy E. Hanson

Series: Chapman & Hall/CRC Texts in Statistical Science

Emphasizing the use of WinBUGS and R to analyze realdata, this text presents statistical tools to address scientif-ic questions. It highlights foundational issues in statistics,the importance of making accurate predictions, and theneed for scientists and statisticians to collaborate in ana-lyzing data. The WinBUGS code provided offers a con-venient platform to model and analyze a wide range ofdata.

Catalog no. K10199, January 2011, 516 pp.ISBN: 978-1-4398-0354-7, $69.95 / £44.99Also available as an eBook








Principles ofUncertaintyJoseph B. KadaneCarnegie Mellon University,Pittsburgh, Pennsylvania, USA


“It's a lovely book, one that I hope will be widely adopt-ed as a course textbook.”—Michael Jordan, University of California, Berkeley, USA

“A careful, complete, and lovingly written exposition ofthe subjective Bayesian viewpoint by one of its most elo-quent and staunch defenders. Summarizes a lifetime oftheory, methods, and application developments for theBayesian inferential engine. A must-read for anyonelooking for a deep understanding of the foundations ofBayesian methods and what they offer modern statisti-cal practice.”

—Bradley P. Carlin, Professor and Head of Division ofBiostatistics, University of Minnesota, Minneapolis, USA

Addressing what are sometimes thought of as two differ-ent subjects, this book presents statistics as simply anapplication of probability. It provides a comprehensiveintroduction to uncertainty principles and the theory ofBayesian statistics. Each chapter begins by introducingone new concept or assumption and then explores theconsequences of that new assumption when added tothose already made.

• Well-written and comprehensive introduction totheory of Bayesian statistics

• Each of the introductory chapters begins by intro-ducing one new concept or assumption

• Uses "just-in-time mathematics" — the introductionto mathematical ideas just before they are applied

• Each chapter ends with a summary and exercises

Selected Contents:

Probability. Conditional Probability and Bayes Theorem.Discrete Random Variables. Probability GeneratingFunctions. Continuous Random Variables.Transformations. Normal Distribution. Making Decisions.Conjugate Analysis. Hierarchical Structuring of a Model.Markov Chain Monte Carlo. Multiparty Problems.Exploration of Old Ideas. Epilogue: Applications.

Catalog no. K12848, May 2011, 503 pp.ISBN: 978-1-4398-6161-5, $89.95 / £57.99

New!

Applied TimeSeries AnalysisWayne A. Woodward andHenry L. GraySouthern Methodist University,Dallas, Texas, USA

Alan C. ElliottUniversity of Texas SouthwesternMedical Center at Dallas, USA

Statistics: A Series of Textbooks and Monographs

Virtually any random process that develops chronologi-cally can be viewed as a time series. This textbook pres-ents real-world examples from the fields of engineering,economics, medicine, biology, and chemistry to promotea solid understanding of the data and associated meth-ods. The text explores many important new methodolo-gies that have developed in time series, such as ARCH andGARCH processes, time varying autocorrelations, timevarying frequencies (TVF), autoregressive processes withtime-dependent coefficients, wavelets, and more. Theauthors also provide a Windows-based time series soft-ware package.

Catalog no. K10965, October 2011, 592 pp.ISBN: 978-1-4398-1837-4, $99.95 / £60.99

Coming Soon!

BayesianModeling ofEcological DataEric ParentENGREF, Paris, France

Etienne RivotFisheries & Aquatic Sciences Center,Rennes Cedex, France


Bayesian statistics are becoming the contemporary stan-dard for treating ecological data. This book is designed forreaders who are interested in the quantitative analysis ofenvironmental data yet reluctant to apply ready-madetechnical recipes without understanding how and whythey work. It focuses on up-to-date ecological issues,including biodiversity, community behavior, andgenomics, and shows how they could be revisited byusing Bayesian modeling techniques. Highly practical, thetext encourages readers to deal with advanced ecologicalissues in practice and to implement models of their own.

Catalog no. C9195, January 2012, c. 352 pp.ISBN: 978-1-58488-919-9, $89.95 / £57.99





9

Computational Statistics


R GraphicsSecond EditionPaul MurrellThe University of Auckland, NewZealandChapman &Hall/CRC The R Series

Praise for the First Edition

“…R Graphics is a must formany useRs and programmmeRs… Paul Murrell, a member of the R Core DevelopmentTeam, has not only been the main author of ‘grid’ buthas also been responsible for several recent enhance-ments to the underlying R graphics engine. Togetherwith its online companion website, this book will be anindispensable resource for almost everyone interested inhow to produce R graphics efficiently and intelligently.”—Martin Maechler, Swiss Federal Institute of Technology, Zurich

“Thanks to Paul Murrell’s new book, the secrets of bothtraditional graphics and the new, modern grid systemget unveiled … a must-have for novices and profession-als alike, the ultimate guide to the power (and beauty)of R graphics.”

—David Meyer, Vienna University of Economics andBusiness Administration, R News

This second edition highlights new graphics-related pack-ages that have been developed, such as the ggplot2package. A number of new chapters cover these packagesin detail. Other chapters new to this edition feature dis-cussions of interactive graphics, 3D graphics, and import-ing graphics. The book also includes new examples aswell as enhanced exercises for teaching or self-study.

Features

• Comprehensive coverage of the core graphicalpackages used in R

• New chapter on ggplot2

• New chapters on applications and extensions of Rgraphics

Selected Contents:

An Introduction to R Graphics. Traditional Graphics:Simple Usage of Traditional Graphics. CustomizingTraditional Graphics. Grid Graphics: Trellis Graphics: thelattice Package. The Grammar of Graphics: the ggplot2Package. The grid Graphics Model. The grid GraphicsObject Model. Developing New Graphics Functions andObjects. The Graphics Engine: Graphics Formats.Graphical Parameters. Graphics Packages: GraphicsExtensions. Plot Extensions. Graphics for CategoricalData. Maps. Node-and-edge Graphs. 3-D Graphics.Dynamic and Interactive Graphics. Importing Graphics.Combining Graphics Systems.


Coming Soon!

StatisticalComputing inC++ and RRandall L. Eubank and Ana KupresaninArizona State University, Tempe, USA

Chapman &Hall/CRC The R Series

Parallel processing can be ideally suited for the solving ofmore complex problems in statistical computing. Thisbook discusses code development in C++ and R, beforegoing beyond to look at the valuable use of these two lan-guages in unison. It covers linear equation solution withregression and linear models motivation, optimizationwith maximum likelihood and nonlinear least squaresmotivation, and random number generation. While thetext does require a working knowledge of both the basicconcepts in statistics and experience in programming, itdoes not require knowledge specific to C++ or R.

Features

• Integrates both C++ and R for the solution of statistical computing problems

• Covers object-oriented programming in both languages

• Uses C++ code in R and R functions in the C++ program

• Presents applications of the C++ Standard TemplateLibrary for statistical computing purposes

• Provides an introduction to parallel processing inC++ and R

Selected Contents:

Introduction. Computer representation of numbers. Asketch of C++. Generation of pseudo-random numbers.Programming in R. Creating classes and methods in R.Numerical linear algebra. Numerical optimization.Abstract data structures. Data structures in C++. Parallelcomputing in C++ and R. An introduction to Unix. Anintroduction to R. C++ library extensions (TR1). TheMatrix and Vector classes. The ranGen class. References.Index.

Catalog no. C6650, December 2011, c. 568 pp.ISBN: 978-1-4200-6650-0, $89.95 / £57.99






Coming Soon!

ProgrammingGraphical UserInterfaces with RJohn VerzaniCUNY/College of Staten Island, NewYork, USA

Michael Lawrence

Chapman &Hall/CRC The R Series

Focusing on graphic user interfaces (GUIs) within the Rlanguage, this book shows programmers and users howto develop their own GUIs, enabling them to interfacewith other languages. The text opens the possibilities ofR’s huge and growing set of statistical methods. Theauthors cover four different packages for writing GUIs:gWidgets, RGtk2, Qt, and Tcl Tk. Supported by a packagein CRAN that contains all of the code along with addi-tional examples, the text is filled with numerous examplesranging from the very simple to detailed illustrations ofhow to code actual interfaces.

Features

• Provides a how-to guide for developing GUIs within R

• Presents the fundamentals for users with limitedknowledge of programming within R and other languages

• Enables R programmers and users to design theirown GUIs for specific functions or as learning tools

• Offers a package in CRAN that contains all of thecode and additional examples

Selected Contents:

The Basic Ideas of Graphical User Interfaces. gWidgets: Overview. Containers. Control Widgets.RGtk2: Overview. Basic Components. Widgets usingModels. Menus and Dialogs. Programming GUIs using Qt.Tcl Tk: Overview. Containers and Layout. Widgets. Web-Based GUIs.

Catalog no. K12672, January 2012, c. 352 pp.ISBN: 978-1-4398-5682-6, $79.95 / £49.99

The R PrimerClaus Thorn EkstromUniversity of Copenhagen,Frederiksberg, Denmark

Newcomers to R are often intimi-dated by the command-line inter-face, the vast number of functionsand packages, or the processes ofimporting data and performing a simple statistical analy-sis. The R Primer provides a collection of concise exam-ples and solutions to R problems frequently encounteredby new users of this statistical software.

Rather than explore the many options available for everycommand as well as the ever-increasing number of pack-ages, the book focuses on the basics of data preparationand analysis and gives examples that can be used as astarting point. The numerous examples illustrate a specif-ic situation, topic, or problem, including data importing,data management, classical statistical analyses, and high-quality graphics production. Each example is self-con-tained and includes R code that can be run exactly asshown, enabling results from the book to be replicated.While base R is used throughout, other functions or pack-ages are listed if they cover or extend the functionality.

After working through the examples found in this text,new users of R will be able to better handle data analysisand graphics applications in R. Additional topics and Rcode are available from the book’s supporting website atwww.statistics.life.ku.dk/primer

Selected Contents:

Importing Data: Reading spreadsheets. Importing datafrom other statistical software programs. Exporting data.

Manipulating Data:Working with data frames. Factors.Transforming variables.

Statistical Analyses: Descriptive statistics. Linear models.Generalized linear models. Methods for analysis ofrepeated measurements. Specific methods. Model vali-dation. Contingency tables. Agreement. Multivariatemethods. Resampling statistics and bootstrapping.Robust statistics. Non-parametric methods. Survivalanalysis.

Graphics: High-level plots. More advanced graphics.Working with graphics.

R: Getting information. R packages. The R workspace.

Bibliography

Index

Catalog no. K12876, August 2011, 299 pp., Soft CoverISBN: 978-1-4398-6206-3, $39.95 / £25.99




11



Coming Soon!

An R Companionto LinearStatistical ModelsChristopher Hay-JahansUniversity of Alaska-Southeast,Juneau, USA

This companion manual was prepared to serve as an Rsupplement for textbooks on Linear Models. The manualprovides computational and coding details on the use ofR that textbooks do not. Topics covered include multiplelinear regression, models for one- and two-factor fixedeffects designs, covariance models, and models for ran-domized complete block designs. The text can serve asboth a course supplement and a fairly detailed self-helpresource. The development of grass-roots code alongsidedemonstrations of pre-packaged routines provides userswith illustrations on how to develop their own code.

Catalog no. K13410, November 2011, c. 373 pp.ISBN: 978-1-4398-7365-6, $79.95 / £49.99

ExploratoryMultivariateAnalysis byExample Using RFrancois Husson, Sebastien Le, and Jerome PagesAGROCAMPUS OUEST, Rennes,France

Series: Chapman & Hall/CRC Computer Science & DataAnalysis

“It is an excellent book which I would strongly recom-mend as a secondary text, supporting or accompanyingthe main text for any advanced undergraduate or grad-uate course in multivariate analysis. … It would supple-ment well any primary textbook in an advanced under-graduate or graduate course in multivariate analysis.”

—MAA Reviews, July 2011

“… a truly excellent [chapter] on clustering … is anexample of what upper-division undergraduate writingshould aspire to. … this enjoyable book and theFactoMineR package are highly recommended for anupper-division undergraduate or beginning graduate-level course in MVA. The acid test for such a work mustbe whether it is likely to spark an interest in studentsand prepare them adequately for more detailed, seriousstudy of the subject and this book easily passes thattest.”

—Journal of Statistical Software, April 2011, Vol. 40

Full of real-world case studies and practical advice, thisbook focuses on four fundamental methods of multivari-ate exploratory data analysis that are most suitable forapplications. It covers principal component analysis whenvariables are quantitative, correspondence analysis andmultiple correspondence analysis when variables are cat-egorical, and hierarchical cluster analysis. Illustrates eachstatistical method with several real-world examples.

Features:

• Contains data sets from different areas of applica-tion, including genomics, marketing, and sensoryanalysis

• Presents methods from a geometric point of viewthat enables new ways to interpret the data

• Uses clustering techniques in a principal compo-nents framework

• Provides data sets and code on the book’s website


Using R for DataManagement,StatisticalAnalysis, andGraphicsNicholas J. HortonSmith College, Northampton,Massachusetts, USA

Ken KleinmanHarvard Medical School, Boston, Massachusetts, USA

This book presents an easy way to learn how to performan analytical task in R. It covers data management,descriptive summaries, inferential procedures, regressionanalysis, multivariate methods, and the creation of graph-ics. The text includes convenient indices organized bytopic and R syntax and contains many example analyses.Data sets and code are available for download on thebook’s website.

Catalog no. K11360, January 2011, 297 pp., Soft CoverISBN: 978-1-4398-2755-0, $59.95 / £38.99Also available as an eBook






Computational Statistics Computational Statistics

Statistical Learning and Data Mining

MultivariateGeneralizedLinear MixedModels Using RDamon M. Berridge andRobert CrouchleyLancaster University, UK

In medical and social scienceresearch, MGLMMs help disentan-gle state dependence from inci-dental parameters. Focusing on these sophisticated dataanalysis techniques, this work presents robust andmethodologically sound models for analyzing large andcomplex data sets—enabling readers to answer increas-ingly complex research questions. It applies the principlesof modeling to longitudinal data from panel and relatedstudies via the Sabre software package in R. Many exam-ples throughout the text illustrate the analysis of real-world data sets.

Supporting materials are available on an associated Sabre-dedi-cated website.


PracticalStatisticalMethodsA SAS ProgrammingApproachLakshmi V. PadgettCentocor, Malvern, Pennsylvania,USA

This book presents a broad spec-trum of statistical methods usefulfor researchers without an extensive statistical back-ground. Omitting mathematical details and complicatedformulae, it provides SAS programs to carry out the nec-essary analyses and draw appropriate inferences for com-mon statistical problems. The author describes methodsused for quantitative data and continuous data followingnormal and nonnormal distributions. She also focuses onsimple linear regression, logistic regression, and the pro-portional hazards model.


New!

Bayesian AnalysisMade SimpleAn Excel GUI forWinBUGSPhil WoodwardPfizer, LTD, Sandwich, Kent, UK

Chapman & Hall/CRC BiostatisticsSeries

This book describes how to use the GUI for WinBUGS—BugsXLA—an Excel add-in written by the author thatallows a range of Bayesian models to be easily specified.With case studies throughout, the text shows how to rou-tinely apply even the more complex aspects of modelspecification, such as GLMMs, outlier robust models, ran-dom effects Emax models, auto-regressive errors, andBayesian variable selection.

Catalog no. K11808, September 2011, 372 pp.ISBN: 978-1-4398-3954-6, $69.95 / £44.99

Data Mining with RLearning with CaseStudiesLuís TorgoUniversity of Porto, Portugal

Chapman & Hall/CRC Data Miningand Knowledge Discovery Series

This hands-on book uses practical examples to illustratethe power of R and data mining. Assuming no priorknowledge of R or data mining/statistical techniques, itcovers a diverse set of problems that pose different chal-lenges in terms of size, type of data, goals of analysis, andanalytical tools. The main data mining processes andtechniques are presented through detailed, real-worldcase studies. With these case studies, the author suppliesall necessary steps, code, and data. Mirroring the do-it-yourself approach of the text, the supporting website pro-vides data sets and R code.







13

Statistical Learning and Data Mining


Second Edition ofa Bestseller!

Bayesian ArtificialIntelligenceSecond EditionKevin B. Korb and Ann E. NicholsonMonash University, Clayton, Victoria,Australia


Updated and expanded, the second edition of this best-seller provides a practical and accessible introduction tothe main concepts, foundation, and applications ofBayesian networks. This edition contains a new chapteron Bayesian network classifiers, along with new applica-tions and case studies. It includes a new section thataddresses foundational problems with causal discoveryand Markov blanket discovery and a new section thatcovers methods of evaluating causal discovery programs.

Supplemental materials are available on the book’s website.


New!

StatisticalLearning andData ScienceEdited by

Mireille Gettler Summa,Leon Bottou, Bernard Goldfarb, Fionn Murtagh, Catherine Pardoux, and Myriam Touati


Various data analysis and statistical learning methodolo-gies have continued to develop to cope with the increas-ing amount of data collected through modern technolo-gy. With a focus on applications, this volume presentscontributions from some of the leading researchers indata analysis. Synthesizing the methodologies into acoherent framework, the book covers a range of topics,from large-scale machine learning to synthesis objectsanalysis.

Catalog no. K13059, October 2011, 227 pp.ISBN: 978-1-4398-6763-1, $89.95 / £57.99

Coming Soon!

A First Course in MachineLearningSimon RogersUniversity of Glasgow, Scotland

Mark GirolamiUniversity College London, UK

Offering a complete introduction to the fundamentalconcepts underlying machine learning theory, this textpresents modern methods and mathematical foundationsneeded to enable further study. Case studies illustrateinteresting applications from engineering, computer sci-ence, and the life sciences. A supporting website providesMATLAB® implementations of all methods described inthe text along with other ancillary material.Solutions manual available upon qualifying course adop-tion


Coming Soon!

Cost-SensitiveMachine LearningEdited by

Balaji Krishnapuram,Shipeng Yu, and R. Bharat RaoSiemens, Malvern, Pennsylvania,USA

The first comprehensive source on cost-sensitive learning,this reference focuses on various research domains inmachine learning that attempt to solve cost-sensitivelearning with simplifying assumptions. The book explicit-ly deals with tradeoffs between the various costs and ben-efits inherent in many domains of machine learningresearch, including semi-supervised learning, active learn-ing, active feature acquisition, and inductive transferlearning. It covers recently developed methods, alongwith several applications of cost-sensitive learning, includ-ing natural language processing, computer vision, med-ical applications, web ads, and marketing.








Data Clusteringin C++An Object-OrientedApproachGuojun GanManulife Financial, Toronto, Canada

Chapman & Hall/CRC Data Miningand Knowledge Discovery Series

Using object-oriented design andprogramming techniques in C++,this book explains how to implement data clusteringalgorithms. The author presents a flexible set of reusableclasses that simplifies the implementation of any dataclustering algorithm. The first part of the text reviewsbasic concepts of data clustering and object-oriented pro-gramming in C++. The second section develops the dataclustering base classes. The third part implements popu-lar data clustering algorithms.

Catalog no. K12884, March 2011, 520 pp.ISBN: 978-1-4398-6223-0, $89.95 / £57.99Also available as an eBook

Clinical Trial DataAnalysis Using RDing-Geng (Din) ChenUniversity of Rochester MedicalCenter, New York, USA

Karl E. PeaceJiann-Ping Hsu, Georgia SouthernUniversity, Statesboro, USA


This book thoroughly covers biostatistical analyses of clin-ical trial data and shows step by step how to implementthe statistical methods using R. Each chapter presentsexamples of clinical trials based on the authors’ actualexperiences in clinical drug development. Various biosta-tistical methods for analyzing the data are then identified.The authors also develop analysis code using appropriateR packages and functions. This approach enables readersto gain an understanding of the analysis methods and Rimplementation so that they can use R to analyze theirown clinical trial data.


Bestseller!

Exploratory DataAnalysis withMATLABSecond EditionWendy L. MartinezThe Department of Defense,Fredericksburg, Virginia, USA

Angel R. MartinezStrayer University, Fredericksburg, Virginia, USA

Jeffrey L. SolkaThe Department of the Navy, Dahlgren, Virginia, USA

Like its bestselling predecessor, this second edition usesnumerous examples and applications to show how EDAmethods are used in practice. This edition covers manyinnovative approaches for dimensionality reduction, clus-tering, and visualization, including nonnegative matrixfactorization, linear discriminant analysis, curvilinear com-ponent analysis, and independent component analysis, aswell as smoothing splines, probabilistic latent semanticanalysis, spectral-based clustering, a rangefinder boxplot,scatterplots with marginal histograms, biplots, andAndrews’ images method. MATLAB® codes are availablefor download on the book’s website.


Coming Soon!

BiostatisticsA Computing ApproachStewart AndersonUniversity of Pittsburgh,Pennsylvania, USA


Focusing on visualization and computational approacheswith an emphasis on the importance of simulation,Biostatistics: A Computing Approach introduces andcompares the usefulness of modern and classical biosta-tistical methods. The book covers essential topics in bio-statistical science, including simple linear regression, mul-tivariate regression, repeated measure, nonparametricanalysis, survival analysis, sample size, and power calcula-tions. Assuming only basic knowledge of probability andstatistics, the text offers numerous practical applicationsand detailed worked examples taken from the medicalarea, all computed using R and SAS, as well as exerciseswith solutions.


Statistical Learning and Data Mining Biostatistics






15

Biostatistics


Exercises andSolutions inBiostatisticalTheoryLawrence L. Kupper, Brian H. Neelon, and Sean M. O'Brien


Drawn from nearly four decades of Lawrence L. Kupper’steaching experiences, this text presents theoretical statis-tical concepts, numerous exercises, and detailed solutionsthat span topics from basic probability to statistical infer-ence. The text links theoretical principles to real-world sit-uations, including some of the authors’ own biostatisticalwork that has addressed complicated design and analysisissues in the health sciences. The authors explain the bio-statistical principles needed to solve the exercises, whichrange in level of difficulty from fairly basic to more chal-lenging.

Catalog no. C7222, January 2011, 420 pp., Soft CoverISBN: 978-1-58488-722-5, $49.95 / £24.99Also available as an eBook

AdvancedBayesian Methods forMedical TestAccuracyLyle D. BroemelingBroemeling and Associates, MedicalLake, Washington, USA


This book covers the advanced topics of verification bias,diagnostic tests with imperfect gold standards, and med-ical tests where no gold standard is available. The authoroffers a practical treatment by including R and WinBugscode in the examples and by employing the Bayesianapproach throughout the text and at the end of eachchapter.


Measures ofInterobserverAgreement andReliabilitySecond EditionMohamed M. ShoukriKing Faisal Specialist Hospital &Research Centre, Riyadh, SaudiArabia

Chapman & Hall/CRC Biostatistics Series

Exploring applications in medical research and clinicalepidemiology, this text continues to cover importantissues related to the design and analysis of reliability andagreement studies. This edition contains a new chapterthat describes various models for methods comparisonstudies as well as a new chapter on the analysis of repro-ducibility using the within-subjects coefficient of variation.It also emphasizes sample size determination and the def-inition of the subjects’ and raters’ population. An accom-panying CD-ROM includes data sets and SAS code.


StatisticalEvaluation ofDiagnosticPerformanceTopics in ROC AnalysisKelly H. Zou, Aiyi Liu,Andriy I. Bandos, Lucila Ohno-Machado, andHoward E. Rockette


This book presents innovative approaches in ReceiverOperating Characteristic (ROC) analysis, which are rele-vant to a wide variety of applications, including medicalimaging, cancer research, epidemiology, and bioinfor-matics. The covered topics include monotone-transfor-mation techniques in parametric ROC analysis, ROCmethods for combined and pooled biomarkers, Bayesianhierarchical transformation models, sequential designsand inferences in the ROC setting, predictive modeling,multireader ROC analysis, and free-response ROC (FROC)methodology.








Biostatistics

Coming Soon!

Adaptive DesignMethods inClinical TrialsSecond EditionShein-Chung ChowDuke University School of Medicine,Durham, North Carolina, USA

Mark ChangAMAG Pharmaceuticals, Inc, Lexington, Massachusetts, USA


This acclaimed book covers the principles and method-ologies in adaptive design and analysis that pertain toadaptations made to trial or statistical procedures basedon accrued data of ongoing clinical trials. It presents awell-balanced summary of current regulatory perspec-tives, recently developed statistical methods, and statisti-cal tests for seamless phase II/III adaptive designs. Thisedition features two new chapters as well as a completerewrite of the chapter on computer simulation. It alsoincludes computer simulations and various case studies toensure a practical understanding of the methodologies.


Adaptive and FlexibleClinical TrialsRichard ChinInstitute for One World Health, SanFrancisco, California, USA

The recent advances in web-basedreal-time data entry and novel sta-tistical methods have made adap-tive clinical trials practical andattractive. Suitable for readers in academia, industry, andgovernment involved in drug development, this is thefirst book that comprehensively explains all essentialaspects of adaptive clinical trials. It discusses, without theuse of highly technical statistical jargon, the design, con-duct, and execution of these trials.


BayesianAdaptiveMethods forClinical TrialsScott M. Berry, Bradley P. Carlin, J. Jack Lee, and Peter Muller


This book explores the growing role of Bayesian thinkingin clinical trial analysis. Covering Phase I, II, and III clinicaltrials, it establishes the basic principles before extendingthem to specific phases and endpoints. The authors alsodiscuss special topics that span different phases of theprocess, including the use of historical data, equivalencestudies, multiplicity and multiple comparisons, and sub-group analysis. They provide many detailed examplesdrawing on real data sets. The R and WinBUGS codesused throughout are available on supporting websites.


Handbook ofAdaptive Designsin Pharmaceuticaland ClinicalDevelopmentEdited by

Annpey PongMerck Research Laboratories,Rahway, New Jersey, USA

Shein-Chung ChowDuke University School of Medicine, Durham, North Carolina,USA

This handbook provides a comprehensive and unifiedpresentation of the principles and latest statisticalmethodologies used when modifying trial proceduresbased on accrued data of ongoing clinical trials. The bookgives a well-balanced summary of current regulatory per-spectives, presents real-world examples of a range ofadaptive designs, and examines issues commonlyencountered when applying adaptive design methods inclinical trials.







17

Biostatistics


Design andAnalysis of Non-Inferiority TrialsMark D. RothmannSilver Springs, Maryland, USA

Brian L. WiensAlcon Laboratories, Fort Worth,Texas, USA

Ivan S.F. ChanMerck & Company, North Wales, Pennsylvania, USA


This book brings together this body of research and con-fronts the issues involved in the design of a non-inferiori-ty trial. Using examples from real clinical trials, the bookdiscusses general and regulatory issues and illustrates howthey affect analysis. Each chapter begins with a non-tech-nical introduction, so the subject is easily understood bythose without prior knowledge of non-inferiority clinicaltrials. The book provides detailed mathematicalapproaches along with their mathematical properties.

Catalog no. C8040, July 2011, 454 pp.ISBN: 978-1-58488-804-8, $89.95 / £57.99

Also available as an eBook

Coming Soon!

RandomizedClinical Trials ofNonpharmacologicTreatmentsEdited by

Isabelle Boutron andPhilippe RavaudINSERM U738, Paris, France

David MoherUniversity of Ottawa, Ontario, Canada


Nonpharmacological treatments include a wide variety oftreatments such as surgery, technical procedures,implantable devices, nonimplantable devices, rehabilita-tion, psychoteherapy, and behavioral interventions. Thisbook focuses on the methods of assessing nonpharmaco-logical treatments, highlighting specific issues and dis-cussing all possible design of trials. It provides practicalexamples to underline the issues and solutions in assess-ing nonpharmacological treatment in trials. Arguably thefirst book to exclusively explore this topic, it discusses var-ious categories of treatments from surgical procedures topsychotherapy.


ControversialStatistical Issues in Clinical TrialsShein-Chung ChowDuke University School of Medicine,Durham, North Carolina, USA


This book covers commonly encountered controversialstatistical issues in clinical trials and, whenever possible,makes recommendations to resolve these problems. Itfocuses on issues occurring at various stages of clinicalresearch and development, including early-phase clinicaldevelopment, bench-to-bedside translational research,and late-phase clinical development. Numerous examplesillustrate the impact of these issues on the evaluation ofthe safety and efficacy of the test treatment under inves-tigation.


Coming Soon!

Handbook ofStatistics inClinical OncologyThird EditionEdited by

John Crowley and Antje HoeringAddressing the many challenges that have arisen sincethe publication of its predecessor, this third edition coversthe newest developments involved in the design andanalysis of cancer clinical trials. Accessible to statisticiansin clinical trials as well as oncologists interested in clinicaltrial methodology, the book presents up-to-date statisticalapproaches to research. New topics in this edition includeBayesian trial design and genome-wide association stud-ies. This edition also contains numerous figures to betterexplain concepts and examples.

Catalog no. K12872, March 2012, c. 700 pp.ISBN: 978-1-4398-6200-1, $119.95 / £76.99







Biostatistics

Monte CarloSimulation for thePharmaceuticalIndustryConcepts, Algorithms,and Case StudiesMark ChangAMAG Pharmaceuticals, Lexington,Massachusetts, USA


Helping you become a skillful "simulator," this book pro-vides broad coverage of the drug development process,from drug discovery to preclinical and clinical trial aspectsto commercialization. It presents the theories and meth-ods for carrying out computer simulations efficiently; cov-ers descriptive and pseudocode algorithms that providethe basis for implementing the simulation methods; andillustrates real-world problems through case studies. Theauthor discusses many key topics, including game theory,adaptive design, molecular design, prescription drugmarketing, biological pathway simulation, genetic pro-gramming, and pharmacokinetic modeling.


FlexibleParametricSurvival AnalysisUsing StataBeyond the Cox ModelPatrick RoystonUniversity College London and MRCClinical Trials Unit, UK

Paul C. LambertUniversity of Leicester, UK

Through real-world case studies, this book shows how touse Stata to estimate a class of flexible parametric survivalmodels. It discusses the modeling of time-dependent andcontinuous covariates and looks at how relative survivalcan be used to measure mortality associated with a par-ticular disease when the cause of death has not beenrecorded. The book describes simple quantification of dif-ferences between any two covariate patterns through cal-culation of time-dependent hazard ratios, hazard differ-ences, and survival differences.

Catalog no. N10372, August 2011, 339 pp., Soft CoverISBN: 978-1-59718-079-5, $79.95 / £49.99

StatisticalThinking inEpidemiologyYu-Kang Tu and Mark S. GilthorpeUniversity of Leeds, UK

Addressing issues that haveplagued researchers throughoutthe last decade, this book providesnew insights into the many exist-ing problems in statistical modeling and offers severalstrategies with which to approach these problems.Emphasizing the importance of statistical thinking behindall analyses, the authors use specific examples in epidemi-ology to illustrate different model specifications that canimply different sets of causal relationships between vari-ables. Each model is interpreted with regard to the con-text of implicit or explicit causal relationships. The authorsalso use vector geometry where applicable to provide anintuitive understanding of important statistical concepts.


DynamicPrediction inClinical SurvivalAnalysisHans van Houwelingenand Hein PutterLeiden University, The Netherlands


In the last twenty years, dynamic prediction models havebeen extensively used to monitor patient prognosis in sur-vival analysis. Written by one of the pioneers in the area,this book synthesizes these developments in a unifiedframework. It covers a range of models, including prog-nostic and dynamic prediction of survival using genomicdata and time-dependent information. The text includesnumerous examples using real data that is taken from theauthors’ collaborative research. R programs are providedfor implementing the methods.

Catalog no. K11593, December 2011, 248 pp.ISBN: 978-1-4398-3533-3, $89.95 / £57.99






19

Statistics in Genetics, Bioinformatics and Computational Biology


New Edition of aBestseller!

Statistics and DataAnalysis forMicroarraysusing R andBioconductorSecond Edition Sorin DraghiciWayne State University, Detroit, Michigan, USA

Series: Chapman & Hall/CRC Mathematical &Computational Biology

Richly illustrated in color, this text provides a clear and rig-orous description of powerful analysis techniques andalgorithms for mining and interpreting biological infor-mation. Omitting tedious details, heavy formalisms, andcryptic notations, the text takes a hands-on, example-based approach that explains the basics of R and microar-ray technology as well as how to choose and apply theproper data analysis tool to specific problems. Now usingR and Bioconductor, this edition has been expanded withfourteen new chapters and 600 more pages. R code isavailable on an accompanying CD-ROM.


Coming Soon!

StochasticModelling forSystems BiologySecond EditionDarren J. WilkinsonSchool of Mathematics andStatistics, Newcastle University, UK

Series: Chapman & Hall/CRCMathematical & Computational Biology

This book provides an accessible introduction to the useof stochastic processes for modeling biological systems,such as genetic and biochemical networks. Focusing onsimulation, the text includes many examples, R and SBMLcode, and a number of computer-based exercises. Fullyupdated, this second edition includes improvements tothe chapters on kinetics and approximate algorithms. Italso greatly expands the coverage of statistical inference,including material on network inference and parameterinference. Updated computing aspects include the use ofthe new SBML Level 3.


Coming Soon!

Time SeriesModeling ofNeuroscienceDataTohru OzakiInstitute of Statistical Mathematics,Tokyo, Japan

This book presents an overview of time series models forthe study of neuroscience data. It is accessible to appliedstatisticians working with neuroscience data as well asquantitatively trained neuroscientists. The book is sup-ported by many real examples to illustrate the methodsprovides computational toolbox on the web, whichenables readers to apply the methods to real data.


Coming Soon!

Statistics of Medical ImagingTianhu LeiUniversity of Pennsylvania &Children's Hospital, Philadelphia,USA

Series: Chapman & Hall/CRCInterdisciplinary Statistics

Providing a unified framework for study, this book reflectsthe extensive work being done in the statistical aspects ofmedical imaging. It presents a complete look at medicalimaging and statistics, from the statistical aspects of imag-ing technology to the statistical analysis of images. It dis-cusses the statistical principles underlying medical imag-ing and offers reference material for researchers involvedin the design of new technology. Illustrations are includ-ed throughout as are many real examples, exercises, andalgorithms.








Statistics in Business, Finance and Economics

Coming Soon!

AppliedOperationalResearch withSASAli Emrouznejad andWilliam HoAston Business School, Birmingham,UK

Designed specifically for SAS users in operational research,this book focuses on the most recent development inSAS/OR optimization, PROC OPTMODEL. It contains awide range of OR optimization problems that demon-strate how the SAS/OR procedures work. It includes sin-gle criterion, project management decision, printed cir-cuit board assembly, and multiple criteria decision makingproblems. Quite possibly the first book to cover the appli-cation of SAS/OR procedures to OR problems, it formu-lates OR problems as various types of mathematical mod-els, including linear programming, integer linear pro-gramming, and global programming models.


New!

Extreme ValueMethods withApplications toFinanceSerguei Y. NovakMiddlesex University, London, UK

Extreme value theory is important for assessing the risk ofhighly unusual events, such as financial market crashes.This book presents a synthesis of research on the field,with emphasis on dependent observations. It covers sev-eral modern topics, such as compound Poisson approxi-mation, that have not been focused on in other books.With examples from finance and insurance to illustratemethods, this book also includes exercises and solutions,making it useful as a self-study tool or a course text.


New!

PracticalSpreadsheet Risk Modeling for ManagementDale Lehman, Huybert Groenendaal, andGreg NolderThis book offers a one-stopresource for performing quantitative risk analyses. Theauthors provide practical case studies along with detailedinstruction and illustration of the features of ModelRisk®,the most advanced risk modeling spreadsheet softwarecurrently available. The specific examples in the textdemonstrate a number of cutting-edge tools and tech-niques that are very powerful in risk analysis but are notavailable in other spreadsheet simulation programs. Thebook covers modeling complex correlations, aggregatinguncertainty and variability, and estimating parameter andmodel uncertainty.


Handbook ofEmpiricalEconomics andFinanceEdited by

Aman UllahUniversity of California, Riverside,USA

David E. A. GilesUniversity of Victoria, British Columbia, Canada


This handbook brings together both background materi-al and new methodological and applied results that areextremely important to the current and future frontiers inempirical economics and finance. Well-recognizedexperts emphasize inferential issues that transpire in theanalysis of cross-sectional, time series, and panel data-based empirical models in economics, finance, and relat-ed disciplines. Containing previously unpublished materi-al on econometrics, the book focuses on micro (cross-sec-tion), macro and financial (time series), and panel datamodels. It provides a balanced viewpoint of differentphilosophical positions and statistical tools.

Catalog no. C7035, January 2011, 532 pp.ISBN: 978-1-4200-7035-4, $149.95 / £95.00Also available as an eBook






21

Statistics in Business, Finance and Economics

Statistics in Engineering and Physical Science


Methods forEstimation andInference inModernEconometricsStanislav AnatolyevNew Economic School, Moscow,Russia

Nikolay GospodinovConcordia University, Montreal, Quebec, Canada

This book covers important topics in econometrics. It dis-cusses methods for efficient estimation in models definedby unconditional and conditional moment restrictions,inference in misspecified models, generalized empiricallikelihood estimators, and alternative asymptotic approx-imations. The first chapter provides a general overview ofestablished nonparametric and parametric approaches toestimation and conventional frameworks for statisticalinference. The next several chapters focus on the estima-tion of models based on moment restrictions implied byeconomic theory. The final chapters cover nonconven-tional asymptotic tools that lead to improved finite-sam-ple inference.


New!

AppliedReliabilityPaul A. TobiasRetired, Austin, Texas, USA

David C. TrindadeSun Microsystems, Inc., Palo Alto,California, USA

This popular book is an easy-to-use guide that addressesbasic descriptive statistics, reliability concepts, the expo-nential distribution, the Weibull distribution, and the log-normal distribution. It also covers reliability data plotting,acceleration models, life test data analysis and systemsmodels, and much more. The third edition includes a newchapter on Bayesian reliability analysis and expanded,updated coverage of repairable system modeling. Takinga practical and example-oriented approach to reliabilityanalysis, this book provides detailed illustrations of soft-ware implementation throughout, using several widelyavailable software packages.

Catalog no. C4665, September 2011, 600 pp.ISBN: 978-1-58488-466-8, $89.95 / £63.99

Coming Soon!

Economic TimeSeriesModeling andSeasonalityEdited by

William R. Bell, Scott H. Holan, and Tucker S. McElroyEdited to ensure a unified viewpoint with common nota-tion and cross-referencing, this practical volume oneconometrics focuses on the key topics of seasonality andmodeling. It covers frequency domain properties of signalextraction filters, the Akaike Information Criterion andmodel selection criteria, diagnostics for seasonal adjust-ment, calendar adjustments of seasonal time series, prop-erties of forecast errors for models with misspecifiedregressors, and generalized airline models for modelingseasonality. Examples, case studies, data, and code areavailable on the book’s web page.

Catalog no. K12089, January 2012, c. 496 pp.ISBN: 978-1-4398-4657-5, $99.95 / £63.99

Coming Soon!

Advanced RiskAnalysis inEngineeringEnterpriseSystemsC. Ariel PintoOld Dominion University, Norfolk,Virginia, USA

Paul R. GarveyThe MITRE Corporation, Bedford, Massachusetts, USA


Presenting a series of advanced topics in modern riskanalysis, this work highlights the modeling, analysis, andmanagement of risk in today’s complex engineeringenterprise systems. Extending far beyond the scope com-mon to traditional systems, it provides a detailed investi-gation of extreme events, including the risks of extremeevents in complex queuing systems. Chapters cover ele-ments of risk and decision theory, analytical framework,risk co-relationships, functional dependency networkanalysis, decision-theoretic algorithms, prioritization sys-tems, and complex queuing systems. Exercises are pro-vided at the end of each chapter.








Statistics for Social and Behavioral Sciences

Coming Soon!

InformativeHypothesesTheory and Practice forBehavioral and SocialScientistsHerbert HoijtinkUniversity Utrecht, The Netherlands

Series: Chapman & Hall/CRCStatistics in the Social and Behavioral Sciences

This detailed book discusses the evaluation of behavioraland social science hypotheses that are more informativethan traditional null and alternative hypotheses. Requiringa minimal prerequisite knowledge of multivariate statis-tics, such as regression and ANOVA, it provides relevantinformation for those doing active research in the socialand behavioral sciences. The book considers Bayesian andclassical approaches and pays considerable attention tosample size determination. Software is available for allfunctions discussed in the book.


Applied SurveyData AnalysisSteven G. Heeringa, Brady T. West, and Patricia A. Berglund

Series: Chapman & Hall/CRCStatistics in the Social and BehavioralSciences

With many examples and exercis-es based on major real-world sur-vey data sets, this book provides a practical statisticaloverview of the analysis of complex sample survey data.It presents many methods and models for survey dataanalysis, including the linear regression, generalized lin-ear, Cox proportional hazards, and discrete time models.Although Stata is used for most examples in the text,other software code is also offered on the book’s website.


Modern Statisticsfor the Social andBehavioralSciencesA PracticalIntroductionRand WilcoxUniversity of Southern California, LosAngeles, USA

Designed for a two-semester, introductory course forgraduate students in the social sciences, this text intro-duces three major insights: 1) justifying normality via thecentral limit theorem can require much larger samplesizes than once thought, 2) the impact of heavy-tailed dis-tributions on power, measures of effect size and measuresof association can be devastating even with large samplesizes, and 3) heteroscedasticity can invalidate classicmethods. Focusing on conceptual issues rather than com-plex computational details. The book also provides alibrary of R functions for applying modern methods thateffectively deal with these insights.

Catalog no. K11557, July 2011, 862 pp.ISBN: 978-1-4398-3456-5, $89.95 / £49.99

New!

Analysis ofQuestionnaireData with RBruno FalissardINSERM U669, Paris, France

Addressing the problem of analy-sis of questionnaire data and inter-pretation of results, this book pro-poses a methodology that uses Rsoftware. The author takes a practical approach to thesubject, presenting principles first followed by detailedexamples of their application to real data. He discussesprinciples of data management and manipulation, andcovers descriptive statistics, statistical modeling, reliability,and missing data. The book focuses on R packages thatare readily available and integrates discussion of theirimplementation and code throughout. All the data setsand R code packages are provided on a website.







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