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Technical Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statisti
Posted on 2010-03-15
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Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statistics) By Jean-Michel Marin, Christian P. Robert, Publisher: Springer
Number Of Pages: 258 Publication Date: 2007-02-02 Sales Rank: 50973 ISBN / ASIN: 0387389792 EAN: 9780387389790 Binding: Hardcover Manufacturer: Springer Studio: Springer Book Description: This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on standard statistical models and backed up by discussed real datasets available from the book website, it provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications. Special attention is paid freeduan.com to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book. While R programs are provided on the book website and R hints are given in the computational sections of the book, The Bayesian Core requires no knowledge of the R language and it can be read and used with any other programming language. The Bayesian Core can be used as a textbook at both undergraduate and graduate levels, as exemplified by courses given at Universit
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