| 期刊全称 | Bayesian Essentials with R | | 影响因子2023 | Jean-Michel Marin,Christian P. Robert | | 视频video | | | 发行地址 | New Complete Solutions Manual for readers available on Springer book page.No prior knowledge of R required to learn the essentials for using it with Bayesian statistics.Each chapter includes exercises | | 学科分类 | Springer Texts in Statistics | | 图书封面 |  | | 影响因子 | .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. 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 Essentials with R .can be used as a textbook at both undergraduate and graduate levels. It is particularly useful with students in professional degree programs and scientists to analyze data the Bayesian way. The text will also enhance introductory courses on Bayesian statistics. Prerequisites fo | | Pindex | Textbook 2014Latest edition |
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发表于 2025-3-21 19:31:08
