A Gamma-Type Distribution with Applications
A Gamma-Type Distribution with Applications
Authors
Iriarte, Yuri A.
Varela, Hector
Gomez, Hector J.
Gomez, Hector W.
Varela, Hector
Gomez, Hector J.
Gomez, Hector W.
Profesor GuĆa
Authors
Date
Datos de publicaciĆ³n:
10.3390/sym12050870
SYMMETRY-BASEL,Vol.12,,2020
SYMMETRY-BASEL,Vol.12,,2020
Tipo de recurso
Article
Keywords
Materia geogrƔfica
Collections
Abstract
This article introduces a new probability distribution capable of modeling positive data that present different levels of asymmetry and high levels of kurtosis. A slashed quasi-gamma random variable is defined as the quotient of independent random variables, a generalized gamma is the numerator, and a power of a standard uniform variable is the denominator. The result is a new three-parameter distribution (scale, shape, and kurtosis) that does not present the identifiability problem presented by the generalized gamma distribution. Maximum likelihood (ML) estimation is implemented for parameter estimation. The results of two real data applications revealed a good performance in real settings.