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doing bayesian data analysis

（出版社）Academic Pr. Doing Bayesian Data Analysis 1冊 978-0-12-405888-0

Doing Bayesian Data Analysis A Tutorial Introduction with R【電子書籍】 John Kruschke

Doing Bayesian Data Analysis: A Tutorial Introduction with R Kruschke， John

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Doing Bayesian Data Analysis A Tutorial with R, JAGS, and Stan【電子書籍】[ John Kruschke ]

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＜p＞＜em＞Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition＜/em＞ provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact high-level scripts that make it easy to run the programs on your own data sets.＜/p＞＜p＞The book is divided into three parts and begins with the basics: models, probability, Bayes’ rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metric-predicted variable on one or two groups; metric-predicted variable w...

（出版社）Academic Pr. Doing Bayesian Data Analysis 1冊 978-0-12-405888-0

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（出版社）Academic　Pr. Doing Bayesian Data Analysis 1冊●著者：Kruschke, John●頁数他：776 p.●装丁：Hard●版次：2nd ed.●出版社：Academic Pr.●発行日：2014/11/17

Doing Bayesian Data Analysis A Tutorial Introduction with R【電子書籍】[ John Kruschke ]

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価格￥8,892

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＜p＞There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and ‘rusty’ calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a lar...

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