02095cam a22003015i 4500
20140709113213.0
130913s2014 nyua b 001 0 eng c
2013950378
1461486866
9781461486862
YDXCP
eng
YDXCP
000SA.161
M337
Marin, Jean-Michel,
Bayesian essentials with R /
Jean-Michel Marin, Christian P. Robert.
Second edition.
xiv, 296 pages :
illustrations (some color) ;
Springer Texts in Statistics,
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.
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.
Bayesian statistical decision theory.
R (Computer program language)
Robert, Christian P.,
1961-,
BK
0
ibc
pccadap
2
ncip
20
y-gencatlg
415824
415824
0
0
ddc
0
0
MAIN
MAIN
2014-07-09
1
000SA.161 M337
134962
2015-07-06
2015-07-03
BK