Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statistics)

✍ Scribed by Jean-Michel Marin, Christian Robert

Publisher: Springer
Year: 2007
Tongue: English
Leaves: 264
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

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