Monte Carlo: Basics
统计力学
2007-05-23 v1
摘要
An introduction to the basics of Monte Carlo is given. The topics covered include, sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, central limit theorem (stable distribution, Levy distribution), random numbers (generation and testing), random sampling techniques (inversion, rejection, sampling from a Gaussian, Metropolis sampling), analogue Monte Carlo and Importance sampling (exponential biasing, spanier technique).
引用
@article{arxiv.cond-mat/0104215,
title = {Monte Carlo: Basics},
author = {K. P. N. Murthy},
journal= {arXiv preprint arXiv:cond-mat/0104215},
year = {2007}
}
备注
74 pages; 16 figures