Advanced Markov chain Monte Carlo methods : learning from past samples /

This book provides comprehensive coverage of simulation of complex systems using Monte Carlo methods. Developing algorithms that are immune to the local trap problem has long been considered as the most important topic in MCMC research. Various advanced MCMC algorithms which address this problem hav...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Liang, F. (Faming), 1970-
Otros Autores: Liu, Chuanhai, 1959-, Carroll, Raymond J.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Chichester, West Sussex : Wiley, 2010.
Temas:
Monte Carlo method.
Markov processes.
Monte Carlo Method
Markov Chains
Méthode de Monte-Carlo.
Processus de Markov.
MATHEMATICS > Numerical Analysis.
Markov processes
Monte Carlo method
dissertations.
Academic theses
Academic theses.
Thèses et écrits académiques.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Advanced Markov Chain Monte Carlo Methods; Contents; Preface; Acknowledgments; Publisher's Acknowledgments; 1 Bayesian Inference and Markov Chain Monte Carlo; 2 The Gibbs Sampler; 3 The Metropolis-Hastings Algorithm; 4 Auxiliary Variable MCMC Methods; 5 Population-Based MCMC Methods; 6 Dynamic Weighting; 7 Stochastic Approximation Monte Carlo; 8 Markov Chain Monte Carlo with Adaptive Proposals; References; Index.

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