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Advanced Markov Chain Monte Carlo Methods (Learning from Past Samples) || Auxiliary Variable MCMC Methods

โœ Scribed by Liang, Faming; Liu, Chuanhai; Carroll, Raymond J.

Publisher
John Wiley & Sons, Ltd
Year
2010
Weight
792 KB
Category
Article
ISBN
0470748265

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Advanced Markov Chain Monte Carlo Method
Advanced Markov Chain Monte Carlo Methods (Learning from Past Samples) || Bayesian Inference and Markov Chain Monte Carlo
โœ Liang, Faming; Liu, Chuanhai; Carroll, Raymond J. ๐Ÿ“‚ Article ๐Ÿ“… 2010 ๐Ÿ› John Wiley & Sons, Ltd โš– 683 KB

Bayesian inference is a probabilistic inferential method. In the last two decades, it has become more popular than ever due to affordable computing power and recent advances in Markov chain Monte Carlo (MCMC) methods for approximating high dimensional integrals. Bayesian inference can be traced bac