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Markov Chain Monte Carlo Simulations...

by Berg Bernd a

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A practical route into Monte Carlo simulation

$112.19 USD
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AlbakiReads Editorial

A practical route into Monte Carlo simulation

Bernd Berg’s text builds its account of Markov chain Monte Carlo from statistical foundations to algorithm design and implementation. It covers Metropolis and heat bath methods, then turns to autocorrelation and ways to assess algorithm performance before introducing multicanonical methods, cluster algorithms, and parallel computing. Web-based Fortran 77 code connects the explanations with numerical examples and gives the book a hands-on dimension; the source notes that the underlying principles also apply to C and C++. The progression makes the material relevant both as a course text and as a reference point for readers developing or examining simulations.

Good fit for readers who enjoy

  • Advanced undergraduate students taking a course in Monte Carlo simulation or statistical methods
  • Researchers working with Monte Carlo methods
  • Programmers seeking simulation examples in Fortran 77, or principles applicable to C and C++

Themes

Markov chain Monte CarloStatistical foundations and algorithm performanceSimulation algorithmsScientific programming

Based on publisher information and book metadata.

Book overview

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++.
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