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Summary Monte Carlo methods often are and always should be part of the normal stock-in-trade of the ordinary practising statistician. This paper is an introduction to such methods, with an emphasis on those that require little or no calculating machinery. Three worked numerical examples, arranged in order of increasing difficulty, illustrate some of the more important general precepts. The last of these examples touches on some problems of self-avoiding walks, i.e., stochastic processes without multiple points.
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Hammersley et al. (Fri,) studied this question.
synapsesocial.com/papers/6a0e63d7686442d1c4c84559 — DOI: https://doi.org/10.1111/j.2517-6161.1954.tb00145.x
J. M. Hammersley
University of Leeds
K. W. Morton
Met Office
Journal of the Royal Statistical Society Series B (Statistical Methodology)
Atomic Energy (Canada)
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