A Doubling Method for the Generalized Lambda Distribution. (7th May 2012) - Headrick, Todd C.; Pant, Mohan D.
Abstract : 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.