| Marin, Jean-Michel, Robert, Christian P. |
Bayesian Core: A Practical Approach to Computational Bayesian Statistics
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Springer, January 2007
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. 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.
Editorial: Springer
Librerías: amazon.com
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