Harris skewed normal distribution

Abstract

In this paper a new family of Harris skewed normal distributions (HSND) is proposed. The probability density function of the HSND can be both positively and negatively skewed, unimodal and multimodal and can be symmetric with heavy tails. Monte Carlo simulations are conducted to evaluate the applicability of the proposed family of distributions. The HSND family is used to fit three different real data sets.

Keywords:

• Harris distribution
• random sums
• moment generating function
• infinite divisible
• maximum likelihood estimators
• EM algorithm

AMS CLASSIFICATION:

• 62E15
• 62F10
• 62H10