A Doubling Method for the Generalized Lambda Distribution

This paper introduces a new family of generalized lambda distributions (GLDs) based on a method of doubling symmetric GLDs. The focus of the development is in the context of L-moments and L-correlation theory. As such, included is the development of a procedure for specifying double GLDs with contro...

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Bibliographic Details
Published in:ISRN applied mathematics 2012-12, Vol.2012 (2012), p.1-19
Main Authors: Headrick, Todd C., Pant, Mohan D.
Format: Article
Language:English
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Summary:This paper introduces a new family of generalized lambda distributions (GLDs) based on a method of doubling symmetric GLDs. The focus of the development is in the context of L-moments and L-correlation theory. As such, included is the development of a procedure for specifying double GLDs with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of settings such as modeling events and Monte Carlo or simulation studies. Further, it is demonstrated that estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to conventional product-moment estimates of skew, kurtosis, and Pearson correlation in terms of both relative bias and efficiency when heavy tailed distributions are of concern.
ISSN:2090-5564
2090-5572
2090-5572
DOI:10.5402/2012/725754