Download PDF by Faming Liang,Chuanhai Liu,Raymond Carroll: Advanced Markov Chain Monte Carlo Methods: Learning from

By Faming Liang,Chuanhai Liu,Raymond Carroll

ISBN-10: 0470748265

ISBN-13: 9780470748268

Markov Chain Monte Carlo (MCMC) equipment at the moment are an crucial instrument in medical computing. This publication discusses contemporary advancements of MCMC equipment with an emphasis on these applying earlier pattern info in the course of simulations. the appliance examples are drawn from varied fields resembling bioinformatics, computing device studying, social technology, combinatorial optimization, and computational physics.

Key Features:

  • Expanded insurance of the stochastic approximation Monte Carlo and dynamic weighting algorithms which are basically resistant to neighborhood seize problems.
  • A certain dialogue of the Monte Carlo Metropolis-Hastings set of rules that may be used for sampling from distributions with intractable normalizing constants.
  • Up-to-date money owed of modern advancements of the Gibbs sampler.
  • Comprehensive overviews of the population-based MCMC algorithms and the MCMC algorithms with adaptive proposals.

This booklet can be utilized as a textbook or a reference publication for a one-semester graduate path in records, computational biology, engineering, and laptop sciences. utilized or theoretical researchers also will locate this booklet beneficial.

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Markov Chain Monte Carlo (MCMC) equipment at the moment are an quintessential device in medical computing. This booklet discusses contemporary advancements of MCMC equipment with an emphasis on these applying earlier pattern details in the course of simulations. the appliance examples are drawn from various fields comparable to bioinformatics, desktop studying, social technological know-how, combinatorial optimization, and computational physics.

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Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples (Wiley Series in Computational Statistics) by Faming Liang,Chuanhai Liu,Raymond Carroll


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