Bayesian essentials with R [electronic resource] / Jean-Michel Marin, Christian P. Robert.

Bayesian essentials with R [electronic resource] / Jean-Michel Marin, Christian P. Robert.

Second edition.

9781461486879 electronic book
1461486874 electronic book
9781461486862

New York : Springer, 2014.

English

1 online resource (xiv, 296 pages) : illustrations (some color).

10.1007/978-1-4614-8687-9 doi

QA279.5

519.5/42

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications. Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. The stakes are high and the reader determines the outcome. 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. In particular, all R codes are discussed with enough detail to make them readily understandable and expandable.

Includes bibliographical references and index.

Access limited to authorized users.

Description based on online resource; title from PDF title page (SpringerLink, viewed November 4, 2013).

Springer texts in statistics, 1431-875X

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