Titlebook: A First Course in Bayesian Statistical Methods; Peter D. Hoff Textbook 2009 Springer-Verlag New York 2009 Markov chain.Statistical Computi

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https://doi.org/10.1007/978-94-007-7557-2We first discuss what properties a reasonable belief function should have, and show that probabilities have these properties. Then, we review the basic machinery of discrete and continuous random variables and probability distributions. Finally, we explore the link between independence and exchangeability.

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Steven Sakiyama,Randolph P. AngleIn the last chapter we saw examples in which a conjugate prior distribution for an unknown parameter θ led to a posterior distribution for which there were simple formulae for posterior means and variances. However, often we will want to summarize other aspects of a posterior distribution.

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Springer Texts in Statisticshttp://image.papertrans.cn/a/image/140748.jpg

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J. Kukkonen,L. Bozó,F. Palmgren,R. S. Sokhition and data description. In this section we give a very brief introduction to the linear regression model and the corresponding Bayesian approach to estimation. Additionally, we discuss the relationship between Bayesian and ordinary least squares regression estimates.

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