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Statistical Rethinking读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 487页 9.3 2020 Chapman and Hall/CRC
定价 出版日期 最近访问 访问指数
USD 99.00 2020-02-20 … 2020-03-08 … 41
主题/类型/题材/标签
统计学,Statistics,统计,贝叶斯,数学,bayesian,机器学习,数据科学,
作者
Richard McElreath      ISBN:9781482253443    原作名/别名:《》
内容和作者简介
Statistical Rethinking摘要

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.

The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.

By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.

作者简介

Richard McElreath is the director of the Department of Human Behavior, Ecology, and Culture at the Max Planck Institute for Evolutionary Anthropology. He is also a professor in the Department of Anthropology at the University of California, Davis. His work lies at the intersection of evolutionary and cultural anthropology, specifically how the evolution of fancy social learning...

本书后续版本
未发行或暂未收录
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