Improving the performance of kurtosis estimator

Authors:
Lihua An;S. Ejaz Ahmed
Affiliations:
Department of Mathematics and Statistics, University of Windsor, Ontario, Canada N9B3P4;Department of Mathematics and Statistics, University of Windsor, Ontario, Canada N9B3P4
Venue:
Computational Statistics & Data Analysis
Year:
2008

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Abstract

In this communication, sample measures of kurtosis adapted by various software packages are compared for data from normal and non-normal populations. Further, two improved estimators of population kurtosis are proposed and their performance is compared with the currently used measures. The suggested estimators have considerably lower mean squared error (MSE) for various sampling designs in our simulation study. Two empirical examples are given to illustrate the usefulness of suggested estimators in practice.