Edited by
David Bailey and Samuel Williams
Textbook
Bayesian Ideas and Data Analysis
Lawrence Berkeley National Laboratory, California, USA
An Introduction for Scientists and Statisticians
Robert Lucas
Ronald Christensen, Wesley O. Johnson, Adam J. Branscum, and Timothy E. Hanson
University of Southern California, Los Angeles, USA Series: Chapman & Hall/CRC Computational Science
Describing useful current research in modern performance science and engineering, this book helps real-world users of parallel computer systems to better understand both the performance vagaries arising in scientific applications and the practical means for improving performance. Some of the most notable experts in the field focus on the areas of performance monitoring, performance analysis, performance modeling, automatic performance tuning, and application tuning. The book also provides an overview of modern computer architecture. It includes examples from such areas as solid mechanics, astrophysics, quantum chromodynamics, molecular dynamics, and environmental science. Catalog no. K10806, ISBN: 978-1-4398-1569-4 December 2010, 6-1/8 x 9-1/4, 399 pp. Suggested Price: $89.95 / £57.99 Available in eBook
Series: Chapman & Hall/CRC Texts in Statistical Science
Emphasizing the use of WinBUGS and R to analyze real data, this text presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to collaborate in analyzing data. The authors cover a large number of statistical models, explore numerical approximations via MCMC simulation, and include numerous exercises and real-world examples. The WinBUGS code provided offers a convenient platform to model and analyze a wide range of data. Code and other materials are available on the book’s website.
Algorithms & Complexity / Computation
Performance Tuning of Scientific Applications
Catalog no. K10199, ISBN: 978-1-4398-0354-7 July 2010, 7 x 10, 516 pp. Suggested Price: $69.95 / £44.99
Textbook
Textbook
Applied Nonparametric Statistical Methods Fourth Edition
Bayesian Methods for Data Analysis Third Edition Bradley P. Carlin
Peter Sprent
University of Minnesota, Minneapolis, USA
Dundee University, Scotland
Thomas A. Louis
Nigel C. Smeeton Guy’s King & St. Thomas School of Medicine, London, UK Series: Chapman & Hall/CRC Texts in Statistical Science
While preserving the clear, accessible style of previous editions, this fourth edition reflects developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. This edition summarizes relevant general statistical concepts and introduces basic ideas of nonparametric or distribution-free methods. Designed experiments, including those with factorial treatment structures, are the focus of an entire chapter. The book also features expanded coverage of the analysis of survival data and the bootstrap method. The final chapter focuses on important modern developments. With numerous exercises, the text offers the student edition of StatXact at a discounted price. Catalog no. C701X, ISBN: 978-1-58488-701-0 March 2007, 6-1/8 x 9-1/4, 544 pp. Suggested Price: $85.95 / £40.99
Johns Hopkins Bloomberg School of Public Health, Maryland, USA Series: Chapman & Hall/CRC Texts in Statistical Science
This proven text provides an accessible introduction to the foundations and applications of Bayesian analysis. Broadening its scope to nonstatisticians, this edition concentrates more on hierarchical Bayesian modeling as implemented via MCMC methods and related data analytic techniques. It contains a state-of-theart, reader-friendly introduction to hierarchical statistical modeling, a chapter on Bayesian design that emphasizes Bayesian clinical trials, an expanded section on ranking and histogram estimation, and a case study on infectious disease modeling and the 1918 flu epidemic. This edition also includes data examples, corresponding R and WinBUGS code, and exercises. Catalog no. C6978, ISBN: 978-1-58488-697-6 June 2008, 6-1/8 x 9-1/4, 552 pp. Suggested Price: $69.95 / £44.99
Textbook
Bayesian Data Analysis Second Edition Andrew Gelman, John B. Carlin, Hal S. Stern, and Donald B. Rubin
Bio-inspired Computing and Networking Yang Xiao
Series: Chapman & Hall/CRC Texts in Statistical Science
The University of Alabama, Tuscaloosa, USA
This second edition of this best-selling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analysis from a Bayesian perspective. Changes in this edition include: additional material on how Bayesian methods are connected to other approaches, stronger focus on MCMC, a chapter on advanced computation topics, more examples, and additional chapters on current models for Bayesian data analysis, such as equation models and generalized linear mixed models. This is both an introductory textbook and a reference that working scientists will use throughout their professional lives.
In seeking new methods to cope with greater communication demands, researchers are finding inspiration in examples presented by nature. Considering a range of sources from insect to primate communication, leading researches present stateof-the-art approaches and novel technologies for developing bio-inspired models. They cover mathematical models and present experimental studies of bio-inspired computing and communications. They explore bio-inspired topology control and reconfiguration methods, as well as bio-inspired localization, synchronization, and mobility approaches. They also delve into such forward-thinking concepts as the evolution and self-healing of network architectures.
Catalog no. C388X, ISBN: 978-1-58488-388-3 July 2003, 6-1/8 x 9-1/4, 696 pp. Suggested Price: $75.95 / £47.99
Catalog no. AU0326, ISBN: 978-1-4200-8032-2 March 2011, 6-1/8 x 9-1/4, 368 pp. Suggested Price: $119.95 / £76.99 Available in eBook
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