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 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.
Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statistics)
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Book Details
Author(s)Jean-Michel Marin, Christian Robert
PublisherSpringer
ISBN / ASIN0387389792
ISBN-139780387389790
Sales Rank807,997
CategoryComputers
MarketplaceUnited States 🇺🇸
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