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The Latest Books in
Computational Statistics from CRC Press
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Contents Computational Methods ......................................3 R Books ................................................................7 Reproducible Research........................................12 Computational Biostatistics ................................13 SAS Books ..........................................................14 Page 7
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Stata Press Books ................................................15 Data Mining ......................................................18 Machine Learning ..............................................21 Business Analytics ..............................................22
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Computational Methods Coming soon!
Linear Models with R Second Edition Julian J. Faraway University of Bath, UK
The world of R has expanded in the ten years that have passed since the first edition of this popular text. This second edition reorganizes the material on interpreting linear models to distinguish the main applications of prediction and explanation. It also covers elementary notions of causality and statistical strategy. New topics include QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates. The author uses the ggplot2 graphics package in addition to base graphics. • Illustrates how linear models are widely used in physical science, engineering, social science, and business applications • Reorganizes the material on interpreting linear models to distinguish the main applications of prediction and explanation • Introduces elementary ideas of causality • Covers QR decomposition, splines, additive models, lasso, multiple imputation, and false discovery rates • Redistributes the topic of statistical strategy throughout the book • Uses base graphics and the ggplot2 graphics package
Selected Contents: Introduction. Estimation. Inference. Prediction. Explanation. Diagnostics. Problems with the Predictors. Problems with the Error. Transformation. Model Selection. Shrinkage Methods. Insurance Redlining—A Complete Example. Missing Data. Categorical Predictors. One Factor Models. Models with Several Factors. Experiments with Blocks. Appendix: About R. Index. Catalog no. K14039, July 2014, c. 286 pp. ISBN: 978-1-4398-8733-2, $89.95 / £57.99 Also available as an eBook
Coming soon!
Linear Mixed Models A Practical Guide Using Statistical Software, Second Edition Brady T. West, Kathleen B. Welch, and Andrzej T. Galecki University of Michigan, Ann Arbor, USA
This second edition updates the case studies using the latest versions of the software procedures, covers additional topics in the application of linear mixed models, and provides up-to-date information on fitting linear mixed models in SAS, SPSS, Stata, R/S-plus, and HLM. This edition presents software procedures capable of fitting models with crossed random effects, uses the lmer() function in the lme4 package in R, fits linear mixed models to complex sample survey data, and discusses Bayesian approaches to making inferences based on linear mixed models. • Covers the current options and features of software procedures for fitting linear mixed models • Adds more practical recommendations on using the software for data analysis • Presents updated graphical procedures in various software packages • Describes power analysis methods for longitudinal and clustered study designs, including software options for power analyses and approaches to writing simulations • Include a new R package that contains all of the data sets • Provides working, up-to-date versions of the software code used for all of the analysis examples on the book’s website
Selected Contents: Introduction. Linear Mixed Models: An Overview. Two-Level Models for Clustered Data: The Rat Pup Example. Three-Level Models for Clustered Data. Models for Repeated-Measures Data: The Rat Brain Example. Random Coefficient Models for Longitudinal Data: The Autism Example. Models for Clustered Longitudinal Data: The Dental Veneer Example. Models for Data with Crossed Random Factors: The SAT Score Example. Appendices. Index. Catalog no. K15924, July 2014, c. 480 pp. ISBN: 978-1-4665-6099-4, $89.95 / £57.99 Also available as an eBook
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Computational Methods The BUGS Book
Coming soon!
Analysis of Categorical Data with R
A Practical Introduction to Bayesian Analysis
Christopher R. Bilder University of Nebraska-Lincoln, USA
Thomas M. Loughin Simon Fraser University, Surrey, British Columbia, Canada
“Through the special attention paid to teaching the basics of R, as well as providing step-by-step particulars in using R in each separate analysis, Bilder and Loughin help establish and promote a group of confident, comfortable users of this software that can seem a mystery to many. I highly and happily recommend this book …” —Deborah J. Rumsey, The Ohio State University
Catalog no. K12597, July 2014, c. 544 pp. ISBN: 978-1-4398-5567-6, $89.95 / £49.99 Also available as an eBook
David Lunn, Chris Jackson, Nicky Best, Andrew Thomas, and David Spiegelhalter “… truly demonstrates the power and flexibility of the BUGS software and its broad range of applications … highly relevant not only for beginners but for advanced users as well. … presents detailed explanations of the underlying models with references to relevant literature [and] worked examples, including excerpts of WinBUGS code, as well as graphical illustrations of results and critical discussions. No doubt, The BUGS Book will become a classic Bayesian textbook and provide invaluable guidance to practicing statisticians, academics, and students alike.” —Renate Meyer, Journal of Biopharmaceutical Statistics, 2014
Catalog no. C8490, October 2012, 399 pp. Soft Cover, ISBN: 978-1-58488-849-9 $52.95 / £25.99 Also available as an eBook
Coming soon!
Coming soon!
Mixed Effects Models for the Population Approach
Bayesian Networks
Models, Tasks, Methods and Tools
With Examples in R Marco Scutari Jean-Baptiste Denis
INRIA Saclay, Orsay, France
Unité de Recherche Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France
This book presents wide-ranging coverage of parametric modeling in linear and nonlinear mixed-effects models. Using these models, readers can perform parameter estimation across a whole population of individuals at the same time. The book takes readers through the whole modeling process, from defining/creating a parametric model to performing tasks on the model using various mathematical methods. It also includes numerous case studies and illustrates the use of the MONOLIX software.
Suitable for graduate students and non-statisticians, this text introduces Bayesian networks using a handson approach with simple yet meaningful examples in R illustrating each step of the modeling process. The book explains the whole process of Bayesian network modeling, from structure learning to parameter learning to inference. It also gives a concise but rigorous treatment of the fundamentals of Bayesian networks, offers an introduction to causal Bayesian networks, and evaluates real-world examples involving causal protein signaling and body composition prediction.
Catalog no. K22488, July 2014, c. 383 pp. ISBN: 978-1-4822-2650-8, $89.95 / £57.99 Also available as an eBook
Catalog no. K22427, July 2014, c. 241 pp. ISBN: 978-1-4822-2558-7, $89.95 / £57.99 Also available as an eBook
Marc Lavielle
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Computational Methods New!
Bayesian Programming Pierre Bessiere, Emmanuel Mazer, Juan Manuel Ahuactzin, and Kamel Mekhnacha "Bayesian Programming comprises a methodology, a programming language, and a set of tools for developing and applying … complex models. … The approach is described in great detail, with many worked examples backed up by an online code repository. Unlike other books that tend to focus almost entirely on mathematics, this one gives equal time to conceptual and methodological guidance for the model-builder.” —Stuart Russell, University of California, Berkeley
Catalog no. K13774, December 2013, 380 pp. ISBN: 978-1-4398-8032-6, $89.95 / £57.99 Also available as an eBook
Flexible Imputation of Missing Data Stef van Buuren TNO Quality of Life, Leiden, The Netherlands
“This book would be well suited as a textbook, especially at the graduate level, possibly for biostatisticians, epidemiologists, or applied scientists and users of statistical methodology. …a very enjoyable read, and—at least in my opinion— it is a book that belongs on everyone’s shelf as it does open one’s eyes to a problem that has surrounded us (and that many of us have ignored!) for a very long time.” —Wolfgang S. Jank, Journal of the American Statistical Association, June 2013
Catalog no. K13103, March 2012, 342 pp. ISBN: 978-1-4398-6824-9, $93.95 / £59.99 Also available as an eBook
Methods of Statistical Model Estimation Joseph M. Hilbe California Institute of Technology, Pasadena, and Arizona State University, Tempe, USA
Andrew P. Robinson University of Melbourne, Parkville, Australia
“With a rich set of R codes, the book contains full demonstration of how to apply the parametric statistical models to obtain desired results of analyses with minimal theoretical details. … a useful reference book for a graduate course on statistical models … many illustrative samples are truly easy to understand. This book is also handy for understanding the algorithm used in statistical model fitting, using the R programming language.” —Jae-kwang Kim, Biometrics, March 2014
Catalog no. K12707, May 2013, 255 pp. ISBN: 978-1-4398-5802-8, $89.95 / £57.99 Also available as an eBook
Handbook of Univariate and Multivariate Data Analysis with IBM SPSS Second Edition Robert Ho Assumption University of Thailand, Bangkok
This accessible handbook explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. Updated with the SPSS statistical package for Windows, this second edition now covers more topics, including tests of assumptions and how to deal with missing data. It also offers three new chapters on multiple discriminant analysis, logistic regression, and canonical correlation and expands coverage of factor analysis, path analysis, and structural equation modeling. Catalog no. K14105, October 2013 ISBN: 978-1-4398-9021-9, $89.95 / £57.99 Also available as an eBook
For more information and complete contents, visit www.crcpress.com
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Computational Methods Clustering
New!
Essentials of Multivariate Data Analysis
A Data Recovery Approach, Second Edition Boris Mirkin
Neil H. Spencer University of Hertfordshire Business School, de Havilland Campus, Hatfield, UK
DCS Birkbeck University of London, UK, and NRU Higher School of Economics, Moscow, Russia
Accessible to students and researchers without a substantial background in statistics or mathematics, this text explains the usefulness of multivariate methods in applied research. Unlike most books on multivariate methods, this one makes straightforward analyses easy to perform for those who are unfamiliar with advanced mathematical formulae. It uses an easily understood dataset to help explain the techniques and an Excel add-in to enable basic analyses, with both available on the book’s CRC Press web page.
Covering both classical and modern approaches, including K-means and divisive clustering, this book uses in-depth case studies to illustrate how clustering methods can be applied. This edition expands and improves the case studies and presents new material on variable selection and weighting, similarity/ relational data clustering, spectral clustering, and interpretation of clusters. A supplementary website provides MATLAB® code and datasets for all of the examples presented in the text.
Catalog no. K19058, December 2013, 186 pp. Soft Cover, ISBN: 978-1-4665-8478-5 $59.95 / £34.99 Also available as an eBook
Catalog no. K11742, October 2012, 374 pp. ISBN: 978-1-4398-3841-9, $104.95 / £66.99 Also available as an eBook
New!
Foundations of Statistical Algorithms
Probability and Statistics for Computer Scientists
With References to R Packages
Second Edition Michael Baron
Claus Weihs, Olaf Mersmann, and Uwe Ligges
University of Texas at Dallas, Richardson, USA
TU Dortmund University, Germany
This text emphasizes recurring themes in all statistical algorithms, including computation, assessment and verification, iteration, intuition, randomness, repetition and parallelization, and scalability. Unique in scope, it touches on topics not usually covered in similar books, namely, systematic verification and the scaling of many established techniques to very large databases. Broadly accessible, it offers examples, exercises, and selected solutions in each chapter. Catalog no. K13688, December 2013, 500 pp. ISBN: 978-1-4398-7885-9, $79.95 / £38.99
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Meeting the ABET requirements for probability and statistics, this text helps readers understand general methods of stochastic modeling, simulation, and data analysis; make optimal decisions under uncertainty; model and evaluate computer systems and networks; and prepare for advanced probability-based courses. The second edition offers a new axiomatic introduction of probability, expanded coverage of statistical inference, more exercises at the end of each chapter, and additional MATLAB® codes, particularly new commands of the Statistics Toolbox. Catalog no. K13525, August 2013, 473 pp. ISBN: 978-1-4398-7590-2, $99.95 / £63.99 Also available as an eBook
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R Books New!
A Handbook of Statistical Analyses using R Third Edition Torsten Hothorn Universtität Zürich, Switzerland
Brian S. Everitt Professor Emeritus, King’s College, London, UK
Like the best-selling first two editions, this third edition provides an up-to-date guide to data analysis using the R system for statistical computing. It explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. Along with more exercises and more detailed explanations of R code, this edition includes three new chapters on quantile regression, missing values, and Bayesian inference. An updated version of the HSAUR package (HSAUR3) is available from CRAN. Catalog no. K21384, June 2014, 448 pp. Soft Cover, ISBN: 978-1-4822-0458-2 $64.95 / £39.99
New!
SAS and R Data Management, Statistical Analysis, and Graphics, Second Edition Ken Kleinman Harvard University, Boston, Massachusetts, USA
Nicholas J. Horton Amherst College, Massachusetts, USA
Retaining the same accessible format as the popular first edition, this book explains how to easily perform an analytical task in both SAS and R. Through the extensive indexing and cross-referencing, users can directly find and implement the material they need. This edition now covers RStudio, a powerful and easyto-use interface for R. Along with extended examples of simulations, it also incorporates a number of additional topics, including APIs, reproducible analysis tools, database management systems, MCMC methods, and finite mixture models. Catalog no. K19040, June 2014, 487 pp. ISBN: 978-1-4665-8449-5, $79.95 / £49.99 Also available as an eBook
New!
New!
Introduction to Scientific Programming and Simulation Using R
Using R for Introductory Statistics
Second Edition Owen Jones, Robert Maillardet, and Andrew Robinson University of Melbourne, Parkville, Australia
With new chapters on ODEs and Markov chains, the second edition of this highly recommended, best-selling book introduces scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data. Requiring no prior knowledge of programming or probability, the book shows them how to turn algorithms into code. It includes case studies that demonstrate the simulation techniques as well as numerous student projects and exercises.
Second Edition John Verzani CUNY/College of Staten Island, New York, USA
Suitable as a primary text or supplement, this best-selling text continues to be the choice for learning R as part of an introductory statistics course. This second edition has been updated with new chapters covering particular features of R, including data management, programming, packages, and RStudio. Along with revised and expanded examples and exercises, it also improves the chapter on categorical data and includes a new chapter on permutation tests. Catalog no. K20484, June 2014, 528 pp. ISBN: 978-1-4665-9073-1, $59.95 / £38.99 Also available as an eBook
Catalog no. K16464, June 2014, 600 pp. ISBN: 978-1-4665-6999-7, $79.95 / £49.99
For more information and complete contents, visit www.crcpress.com
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R Books New!
Coming soon!
Multilevel Modeling Using R
A Handbook of Statistical Graphics Using SAS ODS
W. Holmes Finch and Jocelyn E. Bolin Ball State University, Muncie, Indiana, USA
Ken Kelley
Geoff Der University of Glasgow, Scotland
Brian S. Everitt Professor Emeritus, King’s College, London, UK
University of Notre Dame, Indiana, USA
This book provides a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. The book concludes with Bayesian fitting of multilevel models.
This handbook shows how to use SAS to create many different types of useful statistical graphics for exploring data and diagnosing fitted models. The book focuses on the relatively new SAS ODS graphics, including graphs that are produced routinely via ODS as well as more tailored graphics. Each chapter includes exercises and deals graphically with several sets of data from a wide variety of areas. Catalog no. K20932, August 2014, c. 192 pp. ISBN: 978-1-4665-9903-1, $69.95 / £44.99
Catalog no. K15056, June 2014, 220 pp. Soft Cover, ISBN: 978-1-4665-1585-7 $49.95 / £31.99 Also available as an eBook
Coming soon!
New!
Stated Preference Methods Using R
Using R for Numerical Analysis in Science and Engineering
Hideo Aizaki, Tomoaki Nakatani, and Kazuo Sato
Victor A. Bloomfield University of Minnesota, Minneapolis, USA
This practical guide shows how to use R and its addon packages to obtain numerical solutions to complex mathematical problems commonly faced by scientists and engineers. Providing worked examples and code, the text not only addresses necessary aspects of the R programming language but also demonstrates how to produce useful graphs and statistically analyze and fit data to linear and nonlinear models. It covers Monte Carlo, stochastic, and deterministic methods and explores numerical differentiation and integration, interpolation and curve fitting, and optimization. Catalog no. K13976, May 2014, 359 pp. ISBN: 978-1-4398-8448-5, $89.95 / £57.99 Also available as an eBook
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Suitable for applied statisticians and empirical researchers, this book helps readers select the best method for the quantitative measurement of individual preferences from the many econometric methods available. Providing a practical understanding of these methods, the authors present the theoretical foundations of each method together with worked examples to illustrate their application in various fields, notably empirical economics and market research. R is used to implement all methods, with code, packages, and data sets available online. Catalog no. K14108, August 2014, c. 247 pp. ISBN: 978-1-4398-9047-9, $79.95 / £49.99 Also available as an eBook
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R Books New!
Multiple Factor Analysis by Example Using R Jérôme Pagès Agrocampus-Ouest, Rennes, France
Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of the methodology, this book brings together the theoretical and methodological aspects of MFA. It also covers principal component analysis, multiple correspondence analysis, factor analysis for mixed data, hierarchical MFA, and more. The book also includes examples of applications and details on how to implement MFA using an R package, with the data and R scripts available online. Catalog no. K21451, June 2014, 272 pp. ISBN: 978-1-4822-0547-3, $89.95 / £57.99 Also available as an eBook
New!
Displaying Time Series, Spatial, and Space-Time Data with R Oscar Perpiñán Lamigueiro ETSIDI-UPM, Madrid, Spain
Focusing on the exploration of data with visual methods, this book presents methods and R code for producing high-quality graphics of time series, spatial, and space-time data. It illustrates how to display a dataset starting with an easy and direct approach and progressively adding improvements that involve more complexity. Practical examples using real-world datasets help readers understand how to apply the methods and code. The graphics, data, and R code are accessible from the author’s website. Catalog no. K16087, April 2014, 208 pp. ISBN: 978-1-4665-6520-3, $79.95 / £49.99 Also available as an eBook
The R Student Companion Brian Dennis University of Idaho, Moscow, USA
“An R book for high schoolers! … It may be suitable for non-calculus-based introductory courses at the college level as well. … Dennis does a good job dispelling the ‘steep learning curve’ myth concerning R … It is high time that introductory statistics be taught in an engaging manner that reflects our own enthusiasm for the subject, with meaningful data sets, attractive graphics, and so on. Dennis’s book is a fine contribution toward that goal.” —Norman Matloff, Journal of Statistical Software, February 2013
Catalog no. K13498, September 2012, 360 pp. Soft Cover, ISBN: 978-1-4398-7540-7 $41.95 / £26.99
Analyzing Baseball Data with R Max Marchi Cleveland Indians, Ohio, USA
Jim Albert Bowling Green State University, Ohio, USA
This practical guide provides an accessible introduction to R for sabermetricians, baseball enthusiasts, and students interested in exploring the rich sources of baseball data. It equips readers with the necessary skills and software tools to perform all of the analysis steps, from gathering the datasets and entering them in a convenient format to visualizing the data via graphs to performing a statistical analysis. All of the datasets and R code used in the text are available online. Catalog no. K16473, October 2013, 352 pp. Soft Cover, ISBN: 978-1-4665-7022-1 $39.95 / £25.99
For more information and complete contents, visit www.crcpress.com
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R Books New!
Analyzing Spatial Models of Choice and Judgment with R David A. Armstrong, II, Ryan Bakker, Royce Carroll, Christopher Hare, Keith T. Poole, and Howard Rosenthal This book demonstrates how to estimate and interpret spatial models using a variety of methods with R. In each chapter, the authors explain the basic theory behind the spatial model, illustrate the estimation techniques and explore their historical development, and discuss the advantages and limitations of the methods. They also demonstrate step by step how to implement each method using R with actual datasets. The R code and datasets are available on the book’s website. Catalog no. K15094, February 2014, 352 pp. ISBN: 978-1-4665-1715-8, $69.95 / £44.99 Also available as an eBook
R for Statistics Pierre-André Cornillon, Arnaud Guyader, François Husson, Nicolas Jégou, Julie Josse, Maela Kloareg, Eric Matzner-Lober, and Laurent Rouvière “Section 4.2 on the apply family of functions and related functions for matrices, arrays, and data frames is by far the most friendly and helpful introduction to the subject that I have seen. … All datasets, along with the R code in the book, are available on the website for the text. … If you are not a trained programmer but you aspire to write code that is efficient and perhaps, from time to time, clever, then this book is a fine place for you to start learning R.” —Homer S. White, MAA Reviews, January 2013
Catalog no. K13834, March 2012, 320 pp. Soft Cover, ISBN: 978-1-4398-8145-3 $62.95 / £36.99 Also available as an eBook
New!
The R Primer
Growth Curve Analysis and Visualization Using R
Claus Thorn Ekstrom
Daniel Mirman Moss Rehabilitation Institute, Elkins Park, Pennsylvania, USA
This book provides a practical, easy-to-understand guide to carrying out multilevel regression/growth curve analysis (GCA) of time course or longitudinal data in the behavioral sciences, particularly cognitive science, cognitive neuroscience, and psychology. With a minimum of statistical theory and technical jargon, the author focuses on the concrete issue of applying GCA to behavioral science data and individual differences. Throughout the book, R code illustrates how to implement the analyses and generate the graphs. The example datasets, code, and more are available on the author’s website.
“This book provides a good introduction to R, using a clear layout and detailed, reproducible examples. An ideal tool for any new R user. … A wide range of topics are covered, making the book suitable for a variety of readers, from undergraduate students to professionals new to R. … an extremely helpful introduction to a very useful statistical package.” —Claire Keeble, Journal of Applied Statistics, 2012
Catalog no. K12876, August 2011, 299 pp. Soft Cover, ISBN: 978-1-4398-6206-3 $41.95 / £28.99 Also available as an eBook
Catalog no. K19032, February 2014, 188 pp. ISBN: 978-1-4665-8432-7, $79.95 / £49.99 Also available as an eBook
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R Books Programming Graphical User Interfaces in R Michael Lawrence Genentech Research and Early Development, South San Francisco, California, USA
John Verzani CUNY/College of Staten Island, New York, USA
Focusing on GUIs within the R language, this book shows programmers and users how to develop their own GUIs, enabling them to interface with other languages. The text opens the possibilities of R’s huge and growing set of statistical methods. The authors cover four different packages for writing GUIs: gWidgets, RGtk2, Qt, and Tcl Tk. Supported by a package in CRAN, the text is filled with numerous examples ranging from the very simple to detailed illustrations of how to code actual interfaces. Catalog no. K12672, June 2012, 479 pp. ISBN: 978-1-4398-5682-6, $83.95 / £51.99 Also available as an eBook
Event History Analysis with R Göran Broström Professor Emeritus, Umeå University, Sweden
“… a companion to the R package eha by the same author. … If one wants to analyze such data using R, then the book is well worthwhile. Although it is written more from the point of view of a reader comfortable in using R [and] wanting to learn more about demographic data, it also offers something for the demographers looking to extend the scope of their analyses. … the depth of treatment is about right to form the core of a lecture course …” —Mark Bebbington, Australian & New Zealand Journal of Statistics, 2013
Catalog no. K11534, April 2012, 236 pp., ISBN: 978-1-4398-3164-9, $83.95 / £51.99 Also available as an eBook
R Graphics Second Edition Paul Murrell “… a greatly extended second edition of the well-received 2006 book. The size has almost doubled by adding 12 new chapters … the second edition now contains 19 chapters divided into four parts. … this edition is invaluable and a necessity for everyone who regularly has to produce graphs by using R.” —Stefan K. Lhachimi, Journal of the Royal Statistical Society, Series A, February 2014
Catalog no. K11535, June 2011, 546 pp. ISBN: 978-1-4398-3176-2, $87.95 / £55.99 Also available as an eBook
Statistical Computing in C++ and R Randall L. Eubank and Ana Kupresanin This book discusses code development in C++ and R, before going beyond to look at the valuable use of these two languages in unison. It covers linear equation solution with regression and linear models motivation, optimization with maximum likelihood and nonlinear least squares motivation, and random number generation. Catalog no. C6650, December 2011, 556 pp. ISBN: 978-1-4200-6650-0, $93.95 / £62.99 Also available as an eBook
Multivariate Generalized Linear Mixed Models Using R Damon M. Berridge and Robert Crouchley “… a very well-organised and -written book and therefore I highly recommend it not only to professionals and students but also to applied researchers from many research areas, such as education, psychology, and economics working on complex and large data sets.” —Sebnem Er, Journal of Applied Statistics, 2012
Catalog no. K10680, April 2011, 304 pp. ISBN: 978-1-4398-1326-3, $98.95 / £62.99 Also available as an eBook
For more information and complete contents, visit www.crcpress.com
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Reproducible Research Reproducible Research
New!
Implementing Reproducible Research
Reproducible Research with R and RStudio Christopher Gandrud Hertie School of Governance, Berlin, Germany
Bringing together computational research tools in one accessible source, this book guides readers in creating dynamic and highly reproducible research. Whether an advanced user or just getting started with tools such as R and LaTeX, the book saves readers time searching for information and helps them successfully carry out computational research. It provides a practical reproducible research workflow for gathering and analyzing data as well as dynamically presenting results in print and on the web. Supplementary materials are available on the author’s website. Catalog no. K16624, July 2013, 294 pp., Soft Cover ISBN: 978-1-4665-7284-3, $69.95 / £44.99
Edited by
Victoria Stodden, Friedrich Leisch, and Roger D. Peng This work covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. The book presents contributions from leaders who have developed software and other products that have advanced the field, including Sweave, open source software packages, and good programming practices. Supplementary material is available online. • Covers the three principal areas of reproducible research: tools, practices, and platforms • Explores the use of reproducible research in bioinformatics and large-scale data analyses • Provides case studies and advice on best practices and legal issues, including recommendations of the Reproducible Research Standard Chapters are fully reproducible with material available on the editors’ website.
Dynamic Documents with R and knitr
Selected Contents:
Yihui Xie Iowa State University, Ames, USA
“If you are looking to learn how to use knitr, this book is for you. There are a limited number of resources for learning knitr because the package is relatively new and the documentation produced by Xie is so good. … I think this book will continue to be the best resource about knitr …easy to understand … this is a great read and handy desk reference for the regular knitr user.” —Journal of Statistical Software, January 2014
Catalog no. K21320, July 2013, 216 pp., Soft Cover ISBN: 978-1-4822-0353-0, $59.95 / £38.99
TOOLS: knitr: A Comprehensive Tool for Reproducible Research in R. Reproducibility Using VisTrails. Sumatra: A Toolkit for Reproducible Research. CDE: Automatically Package and Reproduce Computational Experiments. Reproducible Physical Science and the Declaratron. PRACTICES AND GUIDELINES: Developing Open-Source Scientific Practice. Reproducible Bioinformatics Research for Biologists. Reproducible Research for Large-Scale Data Analysis. Practicing Open Science. Reproducibility, Virtual Appliances, and Cloud Computing. The Reproducibility Project: A Model of Large-Scale Collaboration for Empirical Research on Reproducibility—Open Science Collaboration. What Computational Scientists Need to Know about Intellectual Property Law: A Primer. PLATFORMS: Open Science in Machine Learning. RunMyCode.org: A Research-Reproducibility Tool for Computational Sciences. Open Science and the Role of Publishers in Reproducible Research. Index. Catalog no. K15945, April 2014, 448 pp. ISBN: 978-1-4665-6159-5, $79.95 / £49.99 Also available as an eBook
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Computational Biostatistics Joint Models for Longitudinal and Time-to-Event Data With Applications in R Dimitris Rizopoulos Erasmus University Medical Center, Rotterdam, Netherlands
“The book is well written in a matter-of-fact style that makes even unfamiliar readers understand the concept of joint models and furthermore provides them with a guide for getting started with their own analysis. The more joint model-savvy reader will, on the other hand, find inspiration for further foraging into the subject of model extensions, diagnostics, prediction, and accuracy. … a satisfying book on joint models with a solid payout for fellow researchers.” —Maral Saadati, Biometrical Journal, 55, 2013
New!
Foundational and Applied Statistics for Biologists Using R Ken A. Aho Idaho State University, Pocatello, USA
Full of biological applications, exercises, and interactive graphical examples, this text presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable readers to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts. R code and other materials are available online.
Catalog no. K13371, June 2012, 275 pp. ISBN: 978-1-4398-7286-4, $83.95 / £51.99 Also available as an eBook
Catalog no. K13403, December 2013, 618 pp. ISBN: 978-1-4398-7338-0, $69.95 / £44.99 Also available as an eBook
Applied MetaAnalysis with R
New!
Ding-Geng (Din) Chen University of Rochester, New York, USA
Karl E. Peace Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, USA
This book provides detailed, step-by-step explanations of the implementation of meta-analysis methods using R. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, the authors introduce various methods for analyzing meta-data. They then develop analysis code using the appropriate R packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data. Catalog no. K14600, May 2013, 342 pp. ISBN: 978-1-4665-0599-5, $89.95 / £57.99 Also available as an eBook
Bayesian Phylogenetics Methods, Algorithms, and Applications Edited by
Ming-Hui Chen, Lynn Kuo, and Paul O. Lewis University of Connecticut, Storrs, USA
Suitable for graduate-level researchers in statistics and biology, this book presents a snapshot of current trends in Bayesian phylogenetic research. It emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. The book discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. It also covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics. Catalog no. K14380, June 2014, 396 pp. ISBN: 978-1-4665-0079-2, $99.95 / £63.99 Also available as an eBook
For more information and complete contents, visit www.crcpress.com
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SAS Books Coming soon!
Applied Medical Statistics Using SAS
A Handbook of Statistical Graphics Using SAS ODS
Geoff Der University of Glasgow, Scotland
Geoff Der
Brian S. Everitt
University of Glasgow, Scotland
Brian S. Everitt
Professor Emeritus, King’s College, London, UK
“… a well-organized and thorough exploration of broad coverage in medical statistics. The book is an excellent reference of statistical methods with examples of medical data and SAS codes for statisticians or statistical analysts who are working in the medical/clinical area. It also can be a reference book for an introductory or intermediate graduate biostatistics course.” —Jun Zhao, Journal of Biopharmaceutical Statistics, 2014
Professor Emeritus, King’s College, London, UK
This handbook shows how to use SAS to create many different types of useful statistical graphics for exploring data and diagnosing fitted models. The book focuses on the relatively new SAS ODS graphics, including graphs that are produced routinely via ODS as well as more tailored graphics. Each chapter includes exercises and deals graphically with several sets of data from a wide variety of areas.
Catalog no. K13087, October 2012, 559 pp. ISBN: 978-1-4398-6797-6, $93.95 / £59.99 Also available as an eBook
Catalog no. K20932, August 2014, c. 192 pp. ISBN: 978-1-4665-9903-1, $69.95 / £44.99
Handbook of SAS® DATA Step Programming
Nonparametric Methods in Statistics with SAS Applications
Arthur Li City of Hope National Medical Center, Los Angeles County, California, USA
“… a thorough introduction to the statements and functionalities of the SAS DATA step. The book can be used as an introductory tutorial for beginning SAS programmers or as a reference book for experienced users. … Many users of DATA step have a strong statistical background, but not all of them really try to understand DATA step as a programming language. The Handbook of SAS DATA Step Programming covers this gap and helps statisticians improving their programming efficiency using SAS DATA step.” —Journal of Statistical Software, January 2014
Catalog no. K15213, April 2013, 275 pp. ISBN: 978-1-4665-5238-8, $59.95 / £38.99 Also available as an eBook
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Olga Korosteleva California State University, Long Beach, USA
This classroom-tested book teaches how to apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event analysis, density estimation, and resampling methods. Along with exercises at the end of each chapter, the text includes various examples from psychology, education, clinical trials, and other areas. Complete SAS codes for all examples are given in the text. Large data sets for the exercises are available on the author’s website. Catalog no. K18845, August 2013, 195 pp. Soft Cover, ISBN: 978-1-4665-8062-6 $69.95 / £44.99 Also available as an eBook
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Stata Press Books New!
An Introduction to Stata for Health Researchers Fourth Edition Svend Juul and Morten Frydenberg Aarhus University, Denmark
Discovering Structural Equation Modeling Using Stata Revised Edition Alan C. Acock Oregon State University, Corvallis, USA
Updated to correspond to Stata 13, this fourth edition is now written for both Windows and Mac users. It provides improved online documentation, including further reading in online manuals. The book methodically covers data management, simple description and analysis, and more advanced analyses often used in health research, including regression models, survival analysis, and evaluation of diagnostic methods. A chapter on graphics explores most graph types and describes how to modify the appearance of a graph before submitting it for publication.
This practical guide explores all the features of Stata’s sem command. This revised edition includes output, syntax, and instructions for fitting models with the Stata 13 SEM Builder. It shows how this graphical interface allows users to draw publication-quality path diagrams and fit the models without writing any programming code. Each model is presented along with the necessary Stata code. The datasets used are available for download online.
• Presents updated material reflecting Stata version 13
• Includes output, syntax, and instructions for fitting models with the Stata 13 SEM Builder
• Includes advice for both Windows and Mac users
• Requires minimal background in multiple regression and Stata
• Improves documentation sources
• Provides a practical guide for newcomers to structural equation modeling
• Provides many examples, with the datasets available online
• Offers datasets available for download
Selected Contents:
Introduction to Confirmatory Factor Analysis Using Structural Equation Modeling for Path Models Structural Equation Modeling Latent Growth Curves Group Comparisons Epilogue: What Now? Appendices References Indices
Getting Started Getting Help—and More Stata File Types and Names Command Syntax Variables Getting Data in and out of Stata Documentation Commands Calculations Commands Affecting Data Structure Taking Good Care of Your Data Description and Simple Analysis Regression Analysis Time-to-Event Data Measurement and Diagnosis Miscellaneous Graphs Advanced Topics Appendices References Indices
Selected Contents:
Catalog no. N11029, September 2013, 306 pp. Soft Cover, ISBN: 978-1-59718-139-6 $79.95 / £49.99
Catalog no. N11137, March 2014, 346 pp. Soft Cover, ISBN: 978-1-59718-135-8 $79.95 / £49.99
For more information and complete contents, visit www.crcpress.com
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Stata Press Books Introduction to Time Series using Stata
Generalized Linear Models and Extensions
Sean Becketti
Third Edition
This introduction provides a step-by-step guide to essential time series techniques—from the incredibly simple to the quite complex. At the same time, it demonstrates how these techniques can be applied in the Stata statistical package. The book emphasizes understanding the underlying theoretical innovations and the ability to apply them. Real-world examples illustrate the application of each concept. The author highlights the pitfalls and power of each new tool.
James W. Hardin
Catalog no. N10838, January 2013, 741 pp. Soft Cover, ISBN: 978-1-59718-132-7 $79.95 / £49.99
University of South Carolina, Columbia, USA
Joseph M. Hilbe California Institute of Technology, Pasadena, and Arizona State University, Tempe, USA
This book presents a thorough examination of GLM estimation methods as well as the derivation of all major GLM families. The text also contains various models that have been developed on the basis of GLM theory, including GAM, ordered binomial models, multinomial logit and probit models, GEE and other quasi-likelihood models, fixed and random effects models, and random intercept and random parameter models. Using Stata, the book offers numerous examples to assist readers in applying the models to their own data situations. Catalog no. N10590, June 2012, 479 pp. Soft Cover, ISBN: 978-1-59718-105-1 $79.95 / £49.99
Data Analysis Using Stata Third Edition Ulrich Kohler Social Science Research Center, Berlin, Germany
Frauke Kreuter University of Maryland, College Park, USA
A comprehensive introduction to both statistical methods and Stata, this text helps beginners learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. It also offers tips and tricks for readers already familiar with Stata. Step by step, the book leads readers through the entire process of data analysis, covering the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition also explores advanced topics, such as standard errors in complex survey and multiple imputation. Catalog no. N10727, August 2012, 497 pp. Soft Cover, ISBN: 978-1-59718-110-5 $79.95 / £49.99
Multilevel and Longitudinal Modeling Using Stata Volumes I and II, Third Edition Sophia RabeHesketh University of California, Berkeley, USA
Anders Skrondal London School of Economics, UK
This book examines Stata’s treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are mixed because they allow fixed and random effects and they are generalized because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables. Volume I covers continuous Gaussian linear mixed models and Volume II discusses generalized linear mixed models for binary, categorical, count, and survival outcomes. Catalog no. N10560, April 2012, Soft Cover ISBN: 978-1-59718-108-2, $149.95 / £95.00
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Stata Press Books Interpreting and Visualizing Regression Models Using Stata Michael N. Mitchell UCLA Academic Technology Services Consulting Group, Los Angeles, California, USA
This book presents a clear treatment of how to carefully present results from model-fitting in a wide variety of settings. It is accessible to anyone who has to present the tangible meaning of a complex model in a clear fashion, regardless of the audience. As an example, many experienced researchers start to squirm when asked to give a simple explanation of the applied meaning of interactions in nonlinear models, such as logistic regression. The tools in this book make this task much more comprehensible. Catalog no. N10624, April 2012, 558 pp. Soft Cover, ISBN: 978-1-59718-107-5 $79.95 / £49.99
A Gentle Introduction to Stata Revised Third Edition Alan C. Acock Oregon State University, Corvallis, USA
Updated to reflect the new features of Stata 11, this third edition continues to help new Stata users become proficient in Stata. This edition includes a new chapter on the analysis of missing data and the use of multiple-imputation methods. It also provides an extensive revision of the chapter on ANOVA, along with additional material on the application of power analysis. Each chapter includes exercises and real data sets are used throughout. Catalog no. N10594, March 2012, 401 pp. Soft Cover, ISBN: 978-1-59718-109-9 $79.95 / £49.99
A Visual Guide to Stata Graphics Third Edition Michael N. Mitchell UCLA Academic Technology Services Consulting Group, Los Angeles, California, USA
Whether new to Stata graphics or a seasoned veteran, this book teaches users how to use Stata to make publication-quality graphics that will stand out and enhance statistical results. This third edition has been updated and expanded to reflect new Stata graphics features. Along with many more examples, this edition presents new features to specify fonts and symbols. New sections illustrate the use of the marginsplot command and contour plots. Catalog no. N10565, January 2012, 499 pp. Soft Cover, ISBN: 978-1-59718-106-8 $89.95 / £57.99
Bayesian Analysis with Stata John Thompson University of Leicester, UK
This book shows how modern analyses based on MCMC methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Stata’s data management and graphing capability to be used with BUGS speed and reliability. The book emphasizes practical data analysis from the Bayesian perspective and covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of results. Catalog no. N11182, May 2014, 302 pp. Soft Cover, ISBN: 978-1-59718-141-9 $69.95 / £44.99
For more information and complete contents, visit www.crcpress.com
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Data Mining Coming soon!
RapidMiner
Data Classification
Data Mining Use Cases and Business Analytics Applications
Algorithms and Applications
Edited by
Edited by
Markus Hofmann
Charu C. Aggarwal IBM Research, Yorktown Heights, New York, USA
Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, this book explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains, including text, multimedia, social network, and biological data. It presents core methods in data classification, covers recent problem domains, and discusses advanced methods for enhancing the quality of the underlying classification results. Catalog no. K20307, July 2014, c. 705 pp. ISBN: 978-1-4665-8674-1, $89.95 / £57.99 Also available as an eBook
Institute of Technology Blanchardstown, Dublin, Ireland
Ralf Klinkenberg Rapid-I, Dortmund, Germany
Written by leaders in the data mining community, including the developers of the RapidMiner software, this book provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors. The book and software tools cover all relevant steps of the data mining process. The software and their extensions can be freely downloaded at www.RapidMiner.com. Catalog no. K21452, October 2013, 525 pp. ISBN: 978-1-4822-0549-7, $89.95 / £57.99 Also available as an eBook
New!
Data Clustering
Mining User Generated Content
Algorithms and Applications Edited by
Charu C. Aggarwal
Edited by
Marie-Francine Moens, Juanzi Li, and Tat-Seng Chua This volume is the first focused effort to compile state-of-theart research and address future directions of UGC. It explains how to collect, index, and analyze UGC to uncover social trends and user habits. The book describes how to mine various media, including social annotation, music information retrieval, and networks, and discusses the mining and searching of different types of UGC, such as Wikis and blogs. It also presents many applications of UGC, including the use of UGC to answer questions and summarize information. Catalog no. K15468, January 2014, 474 pp. ISBN: 978-1-4665-5740-6, $99.95 / £63.99 Also available as an eBook
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IBM Research, Yorktown Heights, New York, USA
Chandan K. Reddy Wayne State University, Detroit, Michigan, USA
In this book, top researchers from around the world cover the entire area of clustering, from basic methods to more refined and complex data clustering approaches. They pay special attention to recent issues in graphs, social networks, and other domains. The book explores the characteristics of clustering problems in a variety of application areas. It also explains how to glean detailed insight from the clustering process through supervision, human intervention, or the automated generation of alternative clusters. Catalog no. K15510, August 2013, 652 pp. ISBN: 978-1-4665-5821-2, $99.95 / £63.99 Also available as an eBook
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FZN01_5.5x8.5_MC_Temp 5/27/14 9:26 AM Page 19
Data Mining Practical Graph Mining with R Edited by
Nagiza F. Samatova, William Hendrix, John Jenkins, Kanchana Padmanabhan, and Arpan Chakraborty Assuming no prior knowledge of mathematics or data mining, this self-contained book presents a do-it-yourself approach to extracting interesting patterns from graph data. Each chapter focuses on a graph mining task, such as link analysis, cluster analysis, and classification. Through many applications, the book demonstrates how computational techniques can help solve real-world problems. Every algorithm and example is accompanied with R code, allowing readers to see how the algorithmic techniques correspond to the process of graph data analysis and to use the graph mining techniques in practice. Catalog no. K12799, July 2013, 495 pp. ISBN: 978-1-4398-6084-7, $79.95 / £49.99
Computational Intelligent Data Analysis for Sustainable Development Edited by
Ting Yu, Nitesh Chawla, and Simeon Simoff Going beyond performing simple analyses, researchers in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments. This volume presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems. Catalog no. K14261, April 2013, 440 pp. ISBN: 978-1-4398-9594-8, $99.95 / £63.99 Also available as an eBook
ServiceOriented Distributed Knowledge Discovery Domenico Talia and Paolo Trunfio University of Calabria, Rende, Italy
This book presents techniques, algorithms, and systems based on a new approach to distributed largescale data mining, the service-oriented paradigm. It explains how to design services for data analytics, describes real systems for implementing distributed knowledge discovery applications, and explores mobile data mining models. Open source software for developing service-oriented KDD applications is available on the authors’ website. Catalog no. K13494, October 2012, 230 pp. ISBN: 978-1-4398-7531-5, $93.95 / £59.99 Also available as an eBook
Contrast Data Mining Concepts, Algorithms, and Applications Edited by
Guozhu Dong Wright State University, Dayton, Ohio, USA
James Bailey The University of Melbourne, Victoria, Australia
“This book, edited by two leading researchers on contrast mining, and contributed to by over 40 data mining researchers and application scientists, is a comprehensive and authoritative treatment of this research theme. It presents a systematic introduction and a thorough overview of the state of the art for contrast data mining, including concepts, methodologies, algorithms, and applications. … the book will appeal to a wide range of readers …” —Jiawei Han, University of Illinois, Urbana-Champaign
Catalog no. K12517, September 2012, 434 pp. ISBN: 978-1-4398-5432-7, $93.95 / £59.99 Also available as an eBook
For more information and complete contents, visit www.crcpress.com
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Data Mining Ensemble Methods
Data Mining with R
Foundations and Algorithms
Learning with Case Studies
Zhi-Hua Zhou
Luis Torgo
Nanjing University, China
University of Porto, Portugal
“… the book is well structured and written and presents nicely the different ideas and approaches for combining single learners as well as their strengths and limitations.” —Klaus Nordhausen, International Statistical Review, 2013
“Professor Zhou’s book is a comprehensive introduction to ensemble methods in machine learning. … I learned a lot reading it!” —Thomas G. Dietterich, Oregon State University, ACM Fellow, and Founding President of the International Machine Learning Society
“This is a timely book. Right time and right book … with an authoritative but inclusive style that will allow many readers to gain knowledge on the topic.” —Fabio Roli, University of Cagliari
• Supplies the basics for readers unfamiliar with machine learning and pattern recognition • Shows how ensemble methods are used in real-world tasks in computer vision, computer security, medical imaging, and famous data mining competitions, such as the KDD-Cup and Netflix Prize • Presents the theoretical foundations and extensions of many ensemble methods, including boosting, bagging, random trees, and stacking • Covers nearly all aspects of ensemble techniques, such as combination methods and diversity generation methods • Highlights future research directions • Provides additional reading sections in each chapter and references at the back of the book
“This is certainly one of the best books for a direct implementation of data mining algorithms. Another good point of the book is that for most of the problems there are different ways to solve them. … an invaluable resource for data miners, R programmers, as well as people involved in fields such as fraud detection and stock market prediction. If you’re serious about data mining and want to learn from experiences in the field, don’t hesitate!” —Sandro Saitta, Data Mining Research blog, May 2011
“If you want to learn how to analyze your data with a free software package that has been built by expert statisticians and data miners, this is your book. A broad range of real-world case studies highlights the breadth and depth of the R software.” —Bernhard Pfahringer, University of Waikato
“Both R novices and experts will find this a great reference for data mining.” —Intelligent Trading blog and R-bloggers, November 2010
• Illustrates the main data mining techniques through carefully selected case studies • Describes code and approaches that can be easily reproduced or adapted to readers’ own problems • Requires no prior experience with R • Includes introductions to R and MySQL basics • Provides a fundamental understanding of the merits, drawbacks, and analysis objectives of the data mining techniques • Offers data and R code on the author’s website
Selected Contents: Introduction Boosting Bagging Combination Methods Diversity Ensemble Pruning Clustering Ensembles Advanced Topics References Index
Selected Contents:
Catalog no. K11467, June 2012, 236 pp. ISBN: 978-1-4398-3003-1, $83.95 / £51.99 Also available as an eBook
Catalog no. K10510, November 2010, 305 pp. ISBN: 978-1-4398-1018-7, $87.95 / £55.99 Also available as an eBook
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Introduction Predicting Algae Blooms Predicting Stock Market Returns Detecting Fraudulent Transactions Classifying Microarray Samples Bibliography Indices
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Machine Learning New!
Coming soon!
Multilinear Subspace Learning
Regularization, Optimization, Kernels, and Support Vector Machines
Dimensionality Reduction of Multidimensional Data Haiping Lu, Konstantinos N. Plataniotis, and Anastasios Venetsanopoulos Emphasizing essential concepts and system-level perspectives, this book provides a foundation for solving many of today’s most interesting and challenging problems in big multidimensional data processing. It introduces both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. The book follows a unifying MSL framework formulation to systematically derive representative MSL algorithms. It describes various applications of the algorithms, along with their pseudocode. Supporting materials are available online. Catalog no. K12681, December 2013, 296 pp. ISBN: 978-1-4398-5724-3, $89.95 / £57.99 Also available as an eBook
Coming soon!
Machine Learning An Algorithmic Perspective, Second Edition Stephen Marsland Massey University, Palmerston North, New Zealand
Along with updating all chapters and Python code examples, the second edition of this bestseller includes new chapters on Gaussian processes, Boltzmann machines, and deep belief networks. It also revises coverage of kernel methods and adds new material on random forests and model selection. The book retains its popular algorithmic approach as well as its focus on how to use the algorithms that make up machine learning methods and how and why these algorithms work. Catalog no. K18981, October 2014, c. 500 pp. ISBN: 978-1-4665-8328-3, $79.95 / £49.99 Also available as an eBook
Edited by
Johan Suykens, Marco Signoretto, and Andreas Argyriou In this volume, experts present an up-to-date look at large-scale machine learning. They cover the latest research and advances in regularization, sparsity, and compressed sensing; convex and large-scale optimization; and kernel methods and SVMs. Catalog no. K23354, October 2014, c. 400 pp. ISBN: 978-1-4822-4139-6, $89.95 / £57.99 Also available as an eBook
Multi-Label Dimensionality Reduction Liang Sun, Shuiwang Ji, and Jieping Ye This book covers the methodological developments, theoretical properties, computational aspects, and applications of many multi-label dimensionality reduction algorithms, including existing dimensionality reduction algorithms and new developments of traditional algorithms. A supplementary website provides a MATLAB® package for implementing popular dimensionality reduction algorithms. Catalog no. K10304, November 2013, 208 pp. ISBN: 978-1-4398-0615-9, $89.95 / £57.99 Also available as an eBook
Support Vector Machines Optimization Based Theory, Algorithms, and Extensions Naiyang Deng, Yingjie Tian, and Chunhua Zhang Catalog no. K12703, December 2012, 363 pp., ISBN: 978-1-4398-5792-2, $93.95 / £59.99 Also available as an eBook
For more information and complete contents, visit www.crcpress.com
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Business Analytics New!
New!
Business Analytics
Big Data, Mining, and Analytics
An Introduction Edited by
Components of Strategic Decision Making
Jay Liebowitz University of Maryland University College, Adelphi, USA
Stephan Kudyba “Dr. Kudyba has drawn upon his own as well as industry experts’ experiences to create a timely and thought-provoking book on business intelligence. Big Data, Mining, and Analytics should be recommended reading for both industry professionals and students involved in the challenge of developing actionable information. … I highly recommend this book to anyone involved or interested in how big data, data mining, and analytics fit together in our current state …” —Thad Perry, Ph.D., Director of Healthcare Informatics, Tennessee Technological University
• Covers the spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining • Illustrates the value of analytics through numerous practical examples • Facilitates a clear understanding of the concept of big data as well as insight into big data processes and tactics used in decision making • Supplies a conceptual framework for data modeling to help readers improve their decision-making processes
Selected Contents: Introduction to the Big Data Era. Information Creation through Analytics. Big Data Analytics—Architectures, Implementation. Methodology, and Tools. Data Mining Methods and the Rise of Big Data. Data Management and Model Creation Process of Structured Data for Mining and Analytics. The Internet: A Source of New Data for Mining in Marketing. Mining and Analytics in E-Commerce. Streaming Data in the Age of Big Data. Using CEP for Real-Time Data Mining. Transforming Unstructured Data into Useful Information. Mining Big Textual Data. The New Medical Frontier: Real-Time Wireless Medical Data Acquisition for 21st-Century Healthcare and Data Mining Challenges.
This book explains how to use business analytics to sort through an ever-increasing amount of data and improve the decision-making capabilities of an organization. Covering the key areas of business analytics, the book explores the concepts, techniques, applications, and emerging trends that professionals across a wide range of industries need to be aware of. It also examines legal and privacy issues and explores social media in analytics. With this book, readers can develop the understanding required to use big data and high-performance computing in complex environments to improve strategic decision making. • Introduces business analytics concepts, techniques, issues, applications, and emerging trends • Includes software-generic exercises and labs along with answers to labs/exercises • Examines legal and privacy issues • Explores social media in analytics
Selected Contents: The Value of Business Analytics Producing Insights from Information through Analytics Executive/Performance Dashboards Data Mining: Helping to Make Sense of Big Data Big Data Analytics for Business Intelligence Text Mining Fundamentals Neural Network Fundamentals Measuring Success in Social Media: An Information Strategy in a Data Obese World The Legal and Privacy Implications of Data Mining Epilogue: Parting Thoughts about Business Analytics Catalog no. K20757, December 2013, 288 pp. ISBN: 978-1-4665-9609-2, $89.95 / £57.99 Also available as an eBook
Catalog no. K16400, March 2014, 325 pp. ISBN: 978-1-4665-6870-9, $79.95 / £49.99 Also available as an eBook
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Business Analytics New!
Computational Business Analytics Subrata Das Machine Analytics, Inc., Belmont, Massachusetts, USA
This book presents tools and techniques for descriptive, predictive, and prescriptive analytics applicable across multiple domains. The author first covers core descriptive and inferential statistics for analytics and then enhances numerical statistical techniques with symbolic artificial intelligence and machine learning techniques for richer predictive and prescriptive analytics. Through many examples and challenging case studies from a variety of fields, practitioners easily see the connections to their own problems and can then formulate their own solution strategies. Catalog no. K14110, December 2013, 516 pp. ISBN: 978-1-4398-9070-7, $79.95 / £49.99 Also available as an eBook
Getting Started with Business Analytics Insightful DecisionMaking David Roi Hardoon Galit Shmueli Indian School of Business, Hyderabad
“… an interesting ‘how to get started’ book about a contemporary and challenging development in business. … Recommended.” —E.J. Szewczak, CHOICE, August 2013
“A must read for college students and business managers interested in big data and analytics. The book beautifully integrates the business and technology aspects of analytics. It provides in-depth know-how to enable the reader to ‘know’ what and ‘how’ to effectively leverage analytics to deliver business solutions. If you want to get into business analytics, start your journey here!” —Ram D. Gopal, University of Connecticut
Customer and Business Analytics Applied Data Mining for Business Decision Making Using R Daniel S. Putler Alteryx, California, USA
Robert E. Krider Simon Fraser University, Burnaby, British Columbia, Canada
Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities. It explains and demonstrates, via the accompanying opensource software, how advanced analytical tools can address various business problems. The authors also give insight into some of the challenges faced when deploying these tools. Readers can access a powerful, GUI-enhanced customized R package online as well as example data sets on the book’s website. Catalog no. K14501, May 2012, 315 pp. Soft Cover, ISBN: 978-1-4665-0396-0 $73.95 / £46.99 Also available as an eBook
Foundations of Predictive Analytics James Wu and Stephen Coggeshall ID Analytics, San Diego, California, USA
Drawing on the authors’ two decades of experience in applied modeling and data mining, this self-contained book presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It explains the algorithmic details behind each technique and discusses a variety of practical topics that are frequently missing from similar texts. Software and examples are available at www.DataMinerXL.com. Catalog no. K13186, February 2012, 337 pp. ISBN: 978-1-4398-6946-8, $93.95 / £59.99 Also available as an eBook
Catalog no. K14271, March 2013, 190 pp. ISBN: 978-1-4398-9653-2, $59.95 / £38.99
For more information and complete contents, visit www.crcpress.com
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