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An alternate proof for the representation of discrete distributions by equiprobable mixtures

Published online by Cambridge University Press:  14 July 2016

U. Dieter
U. Dieter*
Affiliation:
Technical University of Graz
*
∗ Postal address: Institut für Statistik, Hamerlinggasse 6, A 8010 Graz, Austria.
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Abstract

The paper contains a simple proof that every finite discrete distribution is the equiprobable mixture of r distributions, each of which has at most a mass points.

Keywords

REPRESENTATIONSDISCRETE DISTRIBUTIONSEQUIPROBABLE MIXTURESRANDOM NUMBER GENERATIONALIAS METHOD
Type
Short Communications
Information
Journal of Applied Probability , Volume 19 , Issue 4 , December 1982 , pp. 869 - 872
Copyright
Copyright © Applied Probability Trust 1982 

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Footnotes

Research supported by the Austrian Fonds zur Förderung der wissenschaftlichen Forschung and IBM Corporation.

References

Kronmal, R. A. and Peterson, A. V. (1979) On the alias method for generating random variables from a discrete distribution. Amer. Statistician 33, 214–218.Google Scholar
Peterson, A.V. and Kronmal, R. A. (1980) A representation for discrete distributions by equiprobable mixtures. J. Appl. Prob. 17, 102–111.Google Scholar
Walker, A. J. (1974a) Fast generation of uniformly distributed pseudo random numbers with floating point representation. Electron. Lett. 10, 553–554.Google Scholar
Walker, A. J. (1974b) New fast methods for generating discrete random numbers with arbitrary frequency distribution. Electron. Lett. 10, 127–128.CrossRefGoogle Scholar
Walker, A. J. (1977) An efficient method for generating discrete random variables with general distributions. ACM Trans. Math. Software 3, 253–256.Google Scholar