Bayesian essentials with R / Jean-Michel Marin, Christian P. Robert.
Material type:
- 1461486866
- 9781461486862
- 000SA.161 M337
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
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Books | ISI Library, Kolkata | 000SA.161 M337 (Browse shelf(Opens below)) | Available | 134962 |
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000SA.161 L963 BUGS book a practical introduction to Bayesian analysis | 000SA.161 L987 Introduction to applied Bayesian statistics and estimation for social scientists | 000SA.161 M337 Bayesian core | 000SA.161 M337 Bayesian essentials with R / | 000SA.161 M342 Empirical Bayes methods | 000SA.161 M381 Bayesian Decision problems and Markov chains | 000SA.161 M381 Bayesian Decision problems and Markov chains |
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.
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