Bayesian core : a practical approach to computational Bayesian statistics
著者
書誌事項
Bayesian core : a practical approach to computational Bayesian statistics
（Springer texts in statistics）
Springer, c2007
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注記
Bibliography: p. [247]-249
Includes index
内容説明・目次
内容説明
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.
目次
User's manual.- Normal models.- Regression and variable selection.- Generalised linear models.- Capture-recapture experiments.- Mixture models.- Dynamic models.- Image analysis.
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