A new model for symmetric and skewed data

Authors:
Saralees Nadarajah
Affiliations:
School of mathematics university of manchestermanchester m60 1qd, uk e-mail: saralees.nadarajah@manchester.ac.uk
Venue:
Probability in the Engineering and Informational Sciences
Year:
2008

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Abstract

The Normal and Gamma distributions are the most popular models for analyzing symmetric and skewed data, respectively. In this article, a new multimodal distribution is introduced that contains the Normal and Gamma distributions as particular cases and thus could be a better model for both symmetric and skewed data. Various structural properties of this distribution are derived, including its moment-generating function, characteristic function, moments, entropy, asymptotic distribution of the extreme order statistics, method of moment estimates, maximum likelihood estimates, Fisher information matrix, and simulation issues. The superiority of the new distribution is illustrated by means of two real datasets.