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The variance of a truncated mixed exponential process

Published online by Cambridge University Press:  14 July 2016

Jaimie L. Hebert*
Affiliation:
Appalachian State University
John W. Seaman Jr.*
Affiliation:
Baylor University
*
Postal address: Department of Mathematical Sciences, Appalachian State University, Boone, NC 28608, USA.
∗∗ Postal address: Department of Information Systems, P.O. Box 98005, Baylor University, Waco, TX 76798–8005, USA.

Abstract

Mullooly (1988) provides sufficient conditions under which the variance of a left-truncated, non-negative random variable will be greater than the variance of the original variable. We consider this problem for the class of exponential mixtures, and provide an explicit expression for the inflation in variance in terms of the mixing density.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1994 

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