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Efficient table-free sampling methods for the exponential, Cauchy, and normal distributions

Efficient table-free sampling methods for the exponential, Cauchy, and normal distributions Three algorithms for sampling from exponential, Cauchy and normal distributions are developed. They are based on the "exact approximation" method, and their expected numbers of consumed uniform deviates are less than 1.04 per sample from the target distributions. The algorithms are simple and easily implemented in any desired precision. They require no space for long tables of auxiliary vectors, merely a few constants are needed. Nevertheless, their speed compares well with the performance of much more complex and table-aided sampling procedures. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Communications of the ACM Association for Computing Machinery

Efficient table-free sampling methods for the exponential, Cauchy, and normal distributions

Communications of the ACM , Volume 31 (11) – Nov 1, 1988

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Publisher
Association for Computing Machinery
Copyright
Copyright © 1988 by ACM Inc.
ISSN
0001-0782
DOI
10.1145/50087.50094
Publisher site
See Article on Publisher Site

Abstract

Three algorithms for sampling from exponential, Cauchy and normal distributions are developed. They are based on the "exact approximation" method, and their expected numbers of consumed uniform deviates are less than 1.04 per sample from the target distributions. The algorithms are simple and easily implemented in any desired precision. They require no space for long tables of auxiliary vectors, merely a few constants are needed. Nevertheless, their speed compares well with the performance of much more complex and table-aided sampling procedures.

Journal

Communications of the ACMAssociation for Computing Machinery

Published: Nov 1, 1988

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