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Various representations of a generalized hypergeometric function through statistical techniques

Published online by Cambridge University Press:  24 October 2008

W. J. Anderson
Affiliation:
McGill University, Montreal, Canada
A. M. Mathai
Affiliation:
McGill University, Montreal, Canada

Abstract

This paper deals with a statistical technique of deriving new results on Meijer's G-function. Multiple integral as well as computable series representations are given. The method used is to derive the density of a product of independent beta-distributed random variables by using different statistical techniques, and then compare the expressions to get the desired results. The results obtained in this article do not seem to be available through standard mathematical techniques.

Type
Research Article
Copyright
Copyright © Cambridge Philosophical Society 1984

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References

REFERENCES

[1]Mathai, A. M. and Saxena, R. K.. Generalized Hypergeometric Functions with Applications in Statistics and the Physical Sciences. Lecture Notes in Math. vol. 348 (Springer-Verlag, 1973).Google Scholar
[2]Tretter, M. J. and Walster, G. W.. Central and non-central distributions of Wilks' statistic in MANOVA as mixtures of incomplete beta functions. Ann. Statist. 3 (1975), 467472.Google Scholar
[3]Wald, A. and Brookner, R. J.. On the distribution of Wilks' statistic for testing the independence of several groups of variates. Ann. Math. Statist. 12 (1941), 137152.Google Scholar
[4]Walster, G. W. and Tretter, M. J.. Exact non-central distributions of Wilks' Λ and Wilks-Lawley U criteria as mixtures of incomplete beta functions: for three tests. Ann. Statist. 8 (1980), 13881390.CrossRefGoogle Scholar
[5]Wilks, S. S.. Certain generalizations on the analysis of variance. Biometrika 26 (1932), 471494.Google Scholar