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Titlebook: Bayesian Core: A Practical Approach to Computational Bayesian Statistics; Jean-Michel Marin,Christian P. Robert Textbook 20071st edition S

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Bayesian Core: A Practical Approach to Computational Bayesian Statistics978-0-387-38983-7Series ISSN 1431-875X Series E-ISSN 2197-4136
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https://doi.org/10.1057/978-1-137-56561-7ical side, we present a general MCMC method, the Metropolis–Hastings algorithm, which is used for the simulation of complex distributions where both regular and Gibbs sampling fail. This includes in particular the random walk Metropolis–Hastings algorithm, which acts like a plain vanilla MCMC algorithm.
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Svetoslav Danchev,Grigoris Pavlouo spatial statistics we will provide in this book, and we thus very briefly mention Markov random fields, which are extensions of Markov chains to the spatial domain. A complete reference on this topic is Møller (2003).
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Image Analysis,o spatial statistics we will provide in this book, and we thus very briefly mention Markov random fields, which are extensions of Markov chains to the spatial domain. A complete reference on this topic is Møller (2003).
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1431-875X yesian computing for the most classical models.ComputationalAfter that, it was down to attitude. —Ian Rankin, Black & Blue. — The purpose of this book is to provide a self-contained (we insist!) entry into practical and computational Bayesian statistics using generic examples from the most common mo
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Human Capital and Economic Growththe description of the Bayesian resolution of inferential problems. This being the first chapter, the amount of technical/theoretical material may be a little overwhelming at times. It is, however, necessary to go through these preliminaries before getting to more advanced topics with a minimal number of casualties!
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Normal Models,the description of the Bayesian resolution of inferential problems. This being the first chapter, the amount of technical/theoretical material may be a little overwhelming at times. It is, however, necessary to go through these preliminaries before getting to more advanced topics with a minimal number of casualties!
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