Probability Inequalities for the Sum of Random Variables When Sampling Without Replacement

Jeremy Becnel; Kent Riggs; Dean Young

doi:10.5539/ijsp.v2n4p75

Probability Inequalities for the Sum of Random Variables When Sampling Without Replacement

Research output: Contribution to journal › Article

Abstract

Exponential-type upper bounds are formulated for the probability that the maximum of the partial sample sums of discrete random variables having finite equispaced support exceeds or differs from the population mean by a specified positive constant. The new inequalities extend the work of Serfling (1974). An example of the results are given to demonstrate their efficacy.

Original language	Undefined/Unknown
Journal	Faculty Publications
DOIs	https://doi.org/10.5539/ijsp.v2n4p75
State	Published - Jan 1 2013

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Probability Inequalities for the Sum of Random Variables When Sam

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Cite this

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abstract = "Exponential-type upper bounds are formulated for the probability that the maximum of the partial sample sums of discrete random variables having finite equispaced support exceeds or differs from the population mean by a specified positive constant. The new inequalities extend the work of Serfling (1974). An example of the results are given to demonstrate their efficacy.",

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AB - Exponential-type upper bounds are formulated for the probability that the maximum of the partial sample sums of discrete random variables having finite equispaced support exceeds or differs from the population mean by a specified positive constant. The new inequalities extend the work of Serfling (1974). An example of the results are given to demonstrate their efficacy.

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DO - 10.5539/ijsp.v2n4p75

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