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Data Analysis: A Bayesian Tutorial Devinderjit Sivia, John Skilling
Publisher: Oxford University Press, USA

The book is organized in to three parts. By the way, you might like the book "Data Analysis: A Bayesian Tutorial" by D. Naively speaking, astronomical papers discussing Bayesian analysis mainly serve as Bayesian analysis tutorials in the astronomical subfields of authors' expertise. It has a lot of graphs illustrating the concepts, much like I try to do here. I'll take the argument for why this could be a way to do it from the chapter "Model Selection" in "Data Analysis: A Bayesian Tutorial" by D. He promises the usage of simple examples to explain the techniques of Bayesian analysis. These papers introduce Bayesian analysis They describe well known algorithms such as gibbs sampler, Metropolis-Hasting algorithm, Metropolis algorithms, important sampling, nested sampling, and so forth, and their applications in the astronomical data analysis. Sivia: We have observed some data the forecast of two forecasters A and B. ϼ�2011年刊行，Academic Press, Amsterdam, xviii+653 pp., ISBN:9780123814852 [hbk] → 版元ページ｜著者サイト）. My copy is from 1996 but I think there is a 2nd edition out since then. [新]『Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS』.