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Evaluating Best-Case and Worst-Case Coefficients of Variation when Bounds Are Available

Published online by Cambridge University Press:  27 July 2009

George S. Fishman
Affiliation:
Department of Operations ReserchUniversity fo North Carolina Chapel Hill, North Carolina 27599
David S. Rubin
Affiliation:
Department of Operations ReserchUniversity fo North Carolina Chapel Hill, North Carolina 27599

Abstract

This paper describes a procedure for computing tightest possible best-case and worst-case bounds on the coefficient of variation of a discrete, bounded random variable when lower and upper bounds are available for its unknown probability mass function. An example from the application of the Monte Carlo method to the estimation of network reliability illustrates the procedure and, in particular, reveals considerable tightening in the worst-case bound when compared to the trivial worst-case bound based exclusively on range.

Type
Articles
Copyright
Copyright © Cambridge University Press 1992

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