Journal of Probability and Statistics
Volume 2011 (2011), Article ID 497463, 22 pages
doi:10.1155/2011/497463
Research Article

A Characterization of Power Method Transformations through L-Moments

Section on Statistics and Measurement, Department EPSE, 222-J Wham Building, Mail Code 4618, Southern Illinois University Carbondale, Carbondale, IL 62901, USA

Received 4 July 2010; Revised 27 December 2010; Accepted 20 January 2011

Academic Editor: Rongling Wu

Copyright © 2011 Todd C. Headrick. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Power method polynomial transformations are commonly used for simulating continuous nonnormal distributions with specified moments. However, conventional moment-based estimators can (a) be substantially biased, (b) have high variance, or (c) be influenced by outliers. In view of these concerns, a characterization of power method transformations by L-moments is introduced. Specifically, systems of equations are derived for determining coefficients for specified L-moment ratios, which are associated with standard normal and standard logistic-based polynomials of order five and three. Boundaries for L-moment ratios are also derived, and closed-formed formulae are provided for determining if a power method distribution has a valid probability density function. It is demonstrated that L-moment estimators are nearly unbiased and have relatively small variance in the context of the power method. Examples of fitting power method distributions to theoretical and empirical distributions based on the method of L-moments are also provided.