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Understanding Computational Bayesian Statistics

Written By Bolstad, William
2009, Edition 1
Category: General Statistics
Level: Introductory

John Wiley & Sons Inc.
10475 Crosspoint Blvd.
Indianapolis, New York 46256
United States of America
URL: http://www.wiley.com/WileyCDA/
Phone: 877-762-2974
Fax: 800-597-3299

About This Book

Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics 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.

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