Analyzing Near-Laplace Data with the Epsilon-Skew Laplace Distribution
by
Hassan Elsalloukh
University of Arkansas at Little Rock, Department of Mathematics and Statistics, 2801 S. University Avenue, Little Rock AR 72204-1099

In this paper, I introduce a new distribution family that I name the Epsilon-Skew Laplace Distribution (ESL). This set of random variables possesses both symmetric and asymmetric density functions and includes the Laplace distribution as a special case. I define basic properties and highlight special members of the ESL distribution family. I also derive general expressions for the mean, variance, skewness, kurtosis, moments about zero and about a location parameter, maximum entropy, univariate generator, Fisher Information, score test for symmetry, and maximum likelihood estimation for the three parameters involved in the new distribution. Maximum likelihood estimators are used to fit the data with the epsilon-skew Laplace distribution and compared to studies in which researchers used the Laplace distribution.

Date received: February 14, 2008

Copyright © 2008 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cavi-94.