Bayesian Data Analysis, Second Edition 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Andrew Gelman 作者

Chapman and Hall/CRC

译者

2003-7-29 出版日期

690 页数

USD 83.95 价格

Hardcover

丛书系列

9781584883883 图书编码

Bayesian Data Analysis, Second Edition 在线电子书图书标签: Bayesian Statistics 机器学习统计 Data.Analysis 数学贝叶斯统计学

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发表于2024-12-22

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Bayesian Data Analysis, Second Edition 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Bayesian Data Analysis, Second Edition 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Bayesian Data Analysis, Second Edition 在线电子书用户评价

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不咋地,既没没理论深度，又不系统。既没覆盖足够多的有用算法，废话还多。neither theoretical enough to give deep insight, nor practical and broad enough to cover most useful tools and algorithms. Why it is so famous, always bugs me. Maybe because the author is a much better salesman than a researcher. If you want to know Bayesian, get a real classic, like James O. Berger.

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It must be read if you wish to be a Bayesian

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Bayesian Data Analysis, Second Edition 在线电子书著者简介

Andrew Gelman, John B. Carlin, Hal S. Stern, Donald B. Rubin, David B. Dunson

Bayesian Data Analysis, Second Edition 在线电子书图书目录

Bayesian Data Analysis, Second Edition 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Bayesian Data Analysis, Second Edition 在线电子书图书描述

Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collection Bayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

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