Markov Chain Monte Carlo Simulations and Their Statistical Analysis

With Web-Based Fortran Code

Bernd A. Berg

361 pages, parution le 28/12/2004

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Résumé

This book teaches modern Markov chain Monte Carlo (MC) simulation techniques step by step. The material should be accessible to advanced undergraduate students and is suitable for a course. It ranges from elementary statistics concepts (the theory behind MC simulations), through conventional Metropolis and heat bath algorithms, autocorrelations and the analysis of the performance of MC algorithms, to advanced topics including the multicanonical approach, cluster algorithms and parallel computing. Therefore, it is also of interest to researchers in the field. The book relates the theory directly to Web-based computer code. This allows readers to get quickly started with their own simulations and to verify many numerical examples easily. The present code is in Fortran 77, for which compilers are freely available. The principles taught are important for users of other programming languages, like C or C++.

Key Features

Teaches Markov chain Monte Carlo simulations step by step
Ranges from elementary statistics concepts to advanced Markov chain Monte Carlo simulations
The only book on Monte Carlo simulations for which Web-based computer code allows the reader to verify many numerical examples easily

Sommaire

Preface
Sampling, Statistics and Computer Code
Error Analysis for Independent Random Variables
Markov Chain Monte Carlo
Error Analysis for Markov Chain Data
Advanced Monte Carlo
Parallel Computing
Conclusions, History and Outlook
Appendix A : Computational Supplements
Appendix B : More Exercices and some Solutions
Appendix C : More Fortran Routines
Bibliography
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	World Scientific
Auteur(s)	Bernd A. Berg
Parution	28/12/2004
Nb. de pages	361
Format	16 x 23,5
Couverture	Relié
Poids	672g
Intérieur	Noir et Blanc
EAN13	9789812389350