文件名称:Bayesianmethods
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- 上传时间：2012-11-16
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文件大小：15.63mb
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本压缩文件详细介绍了Robert Piche博士关于贝叶斯算法的理论和他的笔记，其中文档中还包含源码程序，另附两个m文件源程序，是一个非常实用的学习及参考资料-In this course we present the basic principles of Bayesian statistics (an alternative to "orthodox" statistics). We start by learning how to estimate parameters for standard models (normal, binomial, Poisson) and then get acquainted with computational methods (MCMC) and software (WinBUGS) that can solve complicated problems that arise in real applications. Advanced topics include model comparison and decision theory.
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下载文件列表
MAT-51706 Bayesian methods/BayesDental1.pdf
MAT-51706 Bayesian methods/BayesDental2.pdf
MAT-51706 Bayesian methods/GibbsDemo.m
MAT-51706 Bayesian methods/lecture01.pdf
MAT-51706 Bayesian methods/lecture02.pdf
MAT-51706 Bayesian methods/lecture03.pdf
MAT-51706 Bayesian methods/lecture04.pdf
MAT-51706 Bayesian methods/lecture05.pdf
MAT-51706 Bayesian methods/lecture06.pdf
MAT-51706 Bayesian methods/lecture07.pdf
MAT-51706 Bayesian methods/lecture08.pdf
MAT-51706 Bayesian methods/lecture09.pdf
MAT-51706 Bayesian methods/lecture10.pdf
MAT-51706 Bayesian methods/lecture11.pdf
MAT-51706 Bayesian methods/NewcombGibbs.m
MAT-51706 Bayesian methods/notes01.pdf
MAT-51706 Bayesian methods/notes02.pdf
MAT-51706 Bayesian methods/notes03.pdf
MAT-51706 Bayesian methods/notes04.pdf
MAT-51706 Bayesian methods/notes05.pdf
MAT-51706 Bayesian methods/notes06.pdf
MAT-51706 Bayesian methods/notes07.pdf
MAT-51706 Bayesian methods/notes08.pdf
MAT-51706 Bayesian methods/notes09.pdf
MAT-51706 Bayesian methods/notes10.pdf
MAT-51706 Bayesian methods/notes11.pdf
MAT-51706 Bayesian methods/set01.pdf
MAT-51706 Bayesian methods/set02.pdf
MAT-51706 Bayesian methods/set03.pdf
MAT-51706 Bayesian methods/set04.pdf
MAT-51706 Bayesian methods/set05.pdf
MAT-51706 Bayesian methods/set06.pdf
MAT-51706 Bayesian methods/set07.pdf
MAT-51706 Bayesian methods/set08.pdf
MAT-51706 Bayesian methods/set09.pdf
MAT-51706 Bayesian methods/set10.pdf
MAT-51706 Bayesian methods/set11.pdf
MAT-51706 Bayesian methods/SI_Introduction.pdf
MAT-51706 Bayesian methods/sol11.pdf
MAT-51706 Bayesian methods
MAT-51706 Bayesian methods/BayesDental2.pdf
MAT-51706 Bayesian methods/GibbsDemo.m
MAT-51706 Bayesian methods/lecture01.pdf
MAT-51706 Bayesian methods/lecture02.pdf
MAT-51706 Bayesian methods/lecture03.pdf
MAT-51706 Bayesian methods/lecture04.pdf
MAT-51706 Bayesian methods/lecture05.pdf
MAT-51706 Bayesian methods/lecture06.pdf
MAT-51706 Bayesian methods/lecture07.pdf
MAT-51706 Bayesian methods/lecture08.pdf
MAT-51706 Bayesian methods/lecture09.pdf
MAT-51706 Bayesian methods/lecture10.pdf
MAT-51706 Bayesian methods/lecture11.pdf
MAT-51706 Bayesian methods/NewcombGibbs.m
MAT-51706 Bayesian methods/notes01.pdf
MAT-51706 Bayesian methods/notes02.pdf
MAT-51706 Bayesian methods/notes03.pdf
MAT-51706 Bayesian methods/notes04.pdf
MAT-51706 Bayesian methods/notes05.pdf
MAT-51706 Bayesian methods/notes06.pdf
MAT-51706 Bayesian methods/notes07.pdf
MAT-51706 Bayesian methods/notes08.pdf
MAT-51706 Bayesian methods/notes09.pdf
MAT-51706 Bayesian methods/notes10.pdf
MAT-51706 Bayesian methods/notes11.pdf
MAT-51706 Bayesian methods/set01.pdf
MAT-51706 Bayesian methods/set02.pdf
MAT-51706 Bayesian methods/set03.pdf
MAT-51706 Bayesian methods/set04.pdf
MAT-51706 Bayesian methods/set05.pdf
MAT-51706 Bayesian methods/set06.pdf
MAT-51706 Bayesian methods/set07.pdf
MAT-51706 Bayesian methods/set08.pdf
MAT-51706 Bayesian methods/set09.pdf
MAT-51706 Bayesian methods/set10.pdf
MAT-51706 Bayesian methods/set11.pdf
MAT-51706 Bayesian methods/SI_Introduction.pdf
MAT-51706 Bayesian methods/sol11.pdf
MAT-51706 Bayesian methods
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