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On the maximum and its uniqueness for geometric random samples
Published online by Cambridge University Press: 14 July 2016
Abstract
Given n independent, identically distributed random variables, let ρ n denote the probability that the maximum is unique. This probability is clearly unity if the distribution of the random variables is continuous. We explore the asymptotic behavior of the ρ n's in the case of geometric random variables. We find a function Φsuch that (ρ n – Φ(n)) → 0 as n →∞. In particular, we show that ρ n does not converge as n →∞. We derive a related asymptotic result for the expected value of the maximum of the sample. These results arose out of a random depletion model due to Bajaj, which was the original motivation for this paper and which is included.
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- Copyright © Applied Probability Trust 1990
Footnotes
Present address: Department of Mathematics, UCLA, 405 Hilgard Avenue, Los Angeles, CA 90024-1555, USA.
Supported by the Alexander-van-Humboldt Foundation.
Supported under a full-time research assignment from the University of Arkansas.
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