Markov Chain Monte Carlo Simulations And Their Statistical Analysis: With Web-based Fortran Code
暫譯: 馬可夫鏈蒙地卡羅模擬及其統計分析：附網頁版 Fortran 程式碼

Description:

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++.

 

Table of Contents:

• 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