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Doing Bayesian Data Analysis: A Tutorial with R and BUGS John K. Kruschke
Publisher: Academic Press

ϼ�2011年刊行，Academic Press, Amsterdam, xviii+653 pp., ISBN:9780123814852 [hbk] → 版元ページ｜著者サイト）. Traditions & Encounters, Volume | Blog. As a starting point, I'd add Doing Bayesian Data Analysis by John Kruschke and Bayesian Computation with R by Jim Albert to the list . Thus, if your data, y, are Doing Bayesian Data Analysis: # A Tutorial with R THE DATA. –�[新]『Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS』. With R and OpenBUGS Examples (Springer Texts in. Using the log-normal density can be confusing because it's parameterized in terms of the mean and precision of the log-scale data, not the original-scale data. Doing Bayesian Data Analysis: A Tutorial with R and BUGS by John K. All three books use R and BUGS, the standard software for Bayesian work. His well commented R-Code can get you into some simple roll-your-own MCMC and Gibbs sampling and his tutorial-like handling of WinBUGS in the raw and through R2WinBUGS is, I think, the best.