{"product_id":"9780470046098","title":"Understanding Computational Bayesian Statistics","description":"\u003ch3\u003eWiley Series in Computational Statistics\u003c\/h3\u003e\u003ch1\u003eUnderstanding Computational Bayesian Statistics\u003c\/h1\u003e\u003ch3\u003eWilliam M. Bolstad\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ Probability \u0026amp; Statistics \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cb\u003eA hands-on introduction to computational statistics\u003c\/b\u003e \u003cb\u003efrom a Bayesian point of view\u003c\/b\u003e  \u003cp\u003eProviding a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, \u003ci\u003eUnderstanding Computational Bayesian Statistics\u003c\/i\u003e successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistical models, including the multiple linear regression model, the hierarchical mean model, the logistic regression model, and the proportional hazards model.\u003c\/p\u003e \u003cp\u003eThe book begins with an outline of the similarities and differences between Bayesian and the likelihood approaches to statistics. Subsequent chapters present key techniques for using computer software to draw Monte Carlo samples from the incompletely known posterior distribution and performing the Bayesian inference calculated from these samples. Topics of coverage include:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eDirect ways to draw a random sample from the posterior by reshaping a random sample drawn from an easily sampled starting distribution\u003c\/li\u003e \u003cli\u003eThe distributions from the one-dimensional exponential family\u003c\/li\u003e \u003cli\u003eMarkov chains and their long-run behavior\u003c\/li\u003e \u003cli\u003eThe Metropolis-Hastings algorithm\u003c\/li\u003e \u003cli\u003eGibbs sampling algorithm and methods for speeding up convergence\u003c\/li\u003e \u003cli\u003eMarkov chain Monte Carlo sampling\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eUsing numerous graphs and diagrams, the author emphasizes a step-by-step approach to computational Bayesian statistics. At each step, important aspects of application are detailed, such as how to choose a prior for logistic regression model, the Poisson regression model, and the proportional hazards model. A related Web site houses R functions and Minitab macros for Bayesian analysis and Monte Carlo simulations, and detailed appendices in the book guide readers through the use of these software packages.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eUnderstanding Computational Bayesian Statistics\u003c\/i\u003e is an excellent book for courses on computational statistics at the upper-level undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners who use computer programs to conduct statistical analyses of data and solve problems in their everyday work.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e   \u003cp\u003e\u003cb\u003eWILLIAM M. BOLSTAD, P\u003csmall\u003eH\u003c\/small\u003eD,\u003c\/b\u003e is Senior Lecturer in the Department of Statistics at The University of Waikato (New Zealand). Dr. Bolstad's research interests include Bayesian statistics, MCMC methods, recursive estimation techniques, multiprocess dynamic time series models, and forecasting. He is the author of \u003ci\u003eIntroduction to Bayesian Statistics, Second Edition,\u003c\/i\u003e also published by Wiley.  \u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e14 December 2009\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9780470046098\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e336\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e22.24\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44315361640588,"sku":"9780470046098","price":152.95,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9780470046098.jpg?v=1780110687","url":"https:\/\/lateknightbooks.com\/products\/9780470046098","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}