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On unbounded hazard rates for smoothed perturbation analysis

Part of: Stochastic processes Special processes

Published online by Cambridge University Press:  14 July 2016

Michael C. Fu  and
Jian-Qiang Hu
Michael C. Fu*
Affiliation:
University of Maryland
Jian-Qiang Hu*
Affiliation:
Boston University
*
∗Postal address: College of Business and Management, University of Maryland, College Park, MD 20742, USA.
∗∗Postal address: Department of Manufacturing Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA.
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Abstract

Many applications of smoothed perturbation analysis lead to estimators with hazard rate functions of underlying distributions. A key assumption used in proving unbiasedness of the resulting estimator is that the hazard rate function be bounded, a restrictive assumption which excludes all distributions with finite support. Here, we prove through a simple example that this assumption can in fact be removed.

Keywords

DERIVATIVE ESTIMATIONHAZARD RATE

MSC classification

Primary: 60G17: Sample path properties
Secondary: 60K25: Queueing theory
Type
Research Papers
Information
Journal of Applied Probability , Volume 32 , Issue 3 , September 1995 , pp. 659 - 667
Copyright
Copyright © Applied Probability Trust 1995 

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