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Yuri A. Iriarte ; Heleno Bolfarine ;Revista Colombiana de Estadística 2015, 38 2

Autor: Hugo S. Salinas

Fuente: http://www.redalyc.org/


Introducción



Revista Colombiana de Estadística ISSN: 0120-1751 revcoles_fcbog@unal.edu.co Universidad Nacional de Colombia Colombia Salinas, Hugo S.; Iriarte, Yuri A.; Bolfarine, Heleno Slashed Exponentiated Rayleigh Distribution Revista Colombiana de Estadística, vol.
38, núm.
2, julio, 2015, pp.
453-466 Universidad Nacional de Colombia Bogotá, Colombia Available in: http:--www.redalyc.org-articulo.oa?id=89940050009 How to cite Complete issue More information about this article Journals homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative Revista Colombiana de Estadística July 2015, Volume 38, Issue 2, pp.
453 to 466 DOI: http:--dx.doi.org-10.15446-rce.v38n2.51673 Slashed Exponentiated Rayleigh Distribution Distribución Slash Rayleigh exponenciada Hugo S.
Salinas1,a , Yuri A.
Iriarte2,b , Heleno Bolfarine3,c 1 Departamento de Matemática, Facultad de Ingeniería, Universidad de Atacama, Copiapó, Chile 2 Instituto 3 Departamento Tecnológico, Universidad de Atacama, Copiapó, Chile de Estatística, IME, Universidad de Sao Paulo, Sao Paulo, Brasil Abstract In this paper we introduce a new distribution for modeling positive data with high kurtosis.
This distribution can be seen as an extension of the exponentiated Rayleigh distribution.
This extension builds on the quotient of two independent random variables, one exponentiated Rayleigh in the numerator and Beta(q, 1) in the denominator with q 0.
It is called the slashed exponentiated Rayleigh random variable.
There is evidence that the distribution of this new variable can be more flexible in terms of modeling the kurtosis regarding the exponentiated Rayleigh distribution.
The properties of this distribution are studied and the parameter estimates are calculated using the maximum likelihood method.
An application with real data reveals good performance ...





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