TY  - BOOK
AU  - Marin,Jean-Michel
AU  - Robert,Christian P.
TI  - Bayesian essentials with R
T2  - Springer Texts in Statistics,
SN  - 9781461486862 (hbk)
AV  - QA279.5 .M358 2014
PY  - 2014///]
CY  - New York
PB  - Springer
KW  - Bayesian statistical decision theory
KW  - R (Computer program language)
N1  - Includes bibliographical references (pages 287-290) and index; User's manual -- Normal models -- Regression and variable selection -- Generalized linear models -- Capture-recapture experiments -- Mixture models -- Time series -- Image analysis; Also available online
N2  - 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
UR  - http://www.loc.gov/catdir/enhancements/fy1410/2013950378-b.html
UR  - http://www.loc.gov/catdir/enhancements/fy1410/2013950378-t.html
UR  - http://www.loc.gov/catdir/enhancements/fy1410/2013950378-d.html
ER  -