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Retaining the general organization and style of its predecessor, this new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing and computational statistics. Approaching the topic in three major parts–optimization, integration, and smoothing–the book includes an overview section in each chapter introduction and step-by-step implementation summaries to accompany the explanations of key methods; expanded coverage of Monte Carlo sampling and MCMC; a chapter on Alternative Viewpoints; a related Web site; new exercises; and more.
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Retaining the general organization and style of its predecessor, this new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing and computational statistics. Approaching the topic in three major parts–optimization, integration, and smoothing–the book includes an overview section in each chapter introduction and step-by-step implementation summaries to accompany the explanations of key methods; expanded coverage of Monte Carlo sampling and MCMC; a chapter on Alternative Viewpoints; a related Web site; new exercises; and more.