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On unbounded hazard rates for smoothed perturbation analysis
Published online by Cambridge University Press: 14 July 2016
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.
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- Copyright © Applied Probability Trust 1995
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