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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Veröffentlicht in:Symmetry (Basel) Jg. 11; H. 9; S. 1150
Hauptverfasser: Olmos, Neveka M., Venegas, Osvaldo, Gómez, Yolanda M., Iriarte, Yuri A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.09.2019
Schlagworte:
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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Zusammenfassung: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.
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ISSN:2073-8994
2073-8994
DOI:10.3390/sym11091150