A First Course in Monte Carlo
A First Course in Monte Carlo
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发表时间：
2005-10
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通讯作者：
G. S. Fishman
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作者：
G. S. Fishman
蒙特卡洛第一门课程向您展示如何设计、执行和分析基于独立复制、马尔可夫链 MC 和 MC 优化的 MC 实验结果。文本强调了重要性抽样、分层抽样、Rao-Blackwellization、控制变量、对立变量和准随机数等方差减少技术。为了解决优化问题，它描述了几种 MC 技术，包括模拟退火、模拟回火、交换、随机隧道和遗传算法。来自许多领域的例子展示了这些技术在实践中的表现。动手练习让你体验解决实际问题时遇到的挑战。包括选定问题的答案。
A FIRST COURSE IN MONTE CARLO shows you how to design, perform, and analyze the results of MC experiments based on independent replications, Markov chain MC, and MC optimization. The text emphasizes the variance-reducing techniques of importance sampling, stratified sampling, Rao-Blackwellization, control variates, antithetic variates, and quasi-random numbers. For solving optimization problems it describes several MC techniques, including simulated annealing, simulated tempering, swapping, stochastic tunneling, and genetic algorithms. Examples from many areas show how these techniques perform in practice. Hands-on exercises allow you to experience challenges encountered when solving real problems. An answer key to selected problems is included.