Multiple comparisons and sums of dissociated random variables

A. D. Barbour; G. K. Eagleson

doi:10.2307/1427057

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Multiple comparisons and sums of dissociated random variables

A. D. Barbour G. K. Eagleson

Year: 1985 Journal: Advances in Applied Probability Vol: 17 (1)Pages: 147-162 Publisher: Cambridge University Press

DOI: 10.2307/1427057

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Abstract

Sufficient conditions for a sum of dissociated random variables to be approximately normally distributed are derived. These results generalize the central limit theorem for U -statistics and provide conditions which can be verified in a number of applications. The method of proof is that due to Stein (1970).

Keywords:

Mathematics Central limit theorem Random variable Limit (mathematics) Exchangeable random variables Sum of normally distributed random variables Statistics Combinatorics Independent and identically distributed random variables Discrete mathematics Mathematical analysis

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Probability and Risk Models

Social Sciences → Decision Sciences → Management Science and Operations Research

Multiple comparisons and sums of dissociated random variables

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