JSM 2005 - Toronto

Abstract #303896

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 36
Type: Contributed
Date/Time: Sunday, August 7, 2005 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #303896
Title: A Weighted Estimation Method for the Pareto Variance
Author(s): Mei Ling Huang*+ and Percy Brill and Donald Gross
Companies: Brock University and University of Windsor and George Mason University
Address: Department of Mathematics, St Catharines, ON, L2S 3A1, Canada
Keywords: Efficiency ; Mean sqaures error ; Order statistics ; Empirical distribution function
Abstract:

The Pareto distribution is a heavy-tailed distribution with many applications. There are problems for estimating the Pareto variance. This paper uses a weighted empirical distribution function (i.e., level-crossing empirical distribution function [LCEDF]) to estimate the population Pareto variance. An efficiency function of this estimator relative to the classical sample variance estimator is given and studied. Monte Carlo simulation results show the new estimator is more efficient than the classical-moment, maximum-likelihood and other estimators.

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Revised March 2005