An Asymmetric Distribution with Heavy Tails and Its Expectation–Maximization (EM) Algorithm Implementation

In this paper we introduce a new distribution constructed on the basis of the quotient of two independent random variables whose distributions are the half-normal distribution and a power of the exponential distribution with parameter 2 respectively. The result is a distribution with greater kurtosi...

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Published in:	Symmetry (Basel) Vol. 11; no. 9; p. 1150
Main Authors:	Olmos, Neveka M., Venegas, Osvaldo, Gómez, Yolanda M., Iriarte, Yuri A.
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.09.2019
Subjects:	Algorithms Asymmetry Electric power distribution Independent variables Kurtosis Maximization Maximum likelihood estimators Normal distribution Optimization Probability distribution functions Quotients Random variables Skewed distributions
ISSN:	2073-8994, 2073-8994
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Abstract	In this paper we introduce a new distribution constructed on the basis of the quotient of two independent random variables whose distributions are the half-normal distribution and a power of the exponential distribution with parameter 2 respectively. The result is a distribution with greater kurtosis than the well known half-normal and slashed half-normal distributions. We studied the general density function of this distribution, with some of its properties, moments, and its coefficients of asymmetry and kurtosis. We developed the expectation–maximization algorithm and present a simulation study. We calculated the moment and maximum likelihood estimators and present three illustrations in real data sets to show the flexibility of the new model.
AbstractList	In this paper we introduce a new distribution constructed on the basis of the quotient of two independent random variables whose distributions are the half-normal distribution and a power of the exponential distribution with parameter 2 respectively. The result is a distribution with greater kurtosis than the well known half-normal and slashed half-normal distributions. We studied the general density function of this distribution, with some of its properties, moments, and its coefficients of asymmetry and kurtosis. We developed the expectation–maximization algorithm and present a simulation study. We calculated the moment and maximum likelihood estimators and present three illustrations in real data sets to show the flexibility of the new model.
Author	Gómez, Yolanda M. Olmos, Neveka M. Venegas, Osvaldo Iriarte, Yuri A.
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SubjectTerms	Algorithms Asymmetry Electric power distribution Independent variables Kurtosis Maximization Maximum likelihood estimators Normal distribution Optimization Probability distribution functions Quotients Random variables Skewed distributions
Title	An Asymmetric Distribution with Heavy Tails and Its Expectation–Maximization (EM) Algorithm Implementation
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