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Box–Muller transformation
Author(s) -
Scott David W.
Publication year - 2011
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.148
Subject(s) - cumulative distribution function , transformation (genetics) , random number generation , probability density function , simple (philosophy) , algorithm , mathematics , probability distribution , computer science , function (biology) , distribution (mathematics) , statistics , mathematical analysis , biochemistry , chemistry , philosophy , epistemology , gene , evolutionary biology , biology
Abstract The generation of pseudo‐random numbers is critical for modern statistical computing. Given any of the well‐tested pseudo‐random generators for the uniform distribution, the probability integral transform may be employed to provide an exact algorithm for transformation to any desired probability distribution. However, if the cumulative distribution function does not afford a simple form, then this strategy is not effective. In particular, the cumulative distribution function of the normal density is not easy to work within this framework. This article describes the ingenious transformation described by Box and Muller in 1958. WIREs Comp Stat 2011 3 177–179 DOI: 10.1002/wics.148 This article is categorized under: Algorithms and Computational Methods > Random Number Generation