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A New Extension of the Exponential Distribution
Una nueva extensión de la distribución exponencial
DOI:
https://doi.org/10.15446/rce.v37n1.44355Keywords:
Exponential distribution, Mixtures of distribution, Likelihood (en)distribución exponencial, mezcla de distribuciones, verosimilitud (es)
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The present paper considers an extension of the exponential distribution based on mixtures of positive distributions. We study the main properties of this new distribution, with special emphasis on its moments, moment generator function and some characteristics related to reliability studies. We also discuss parameter estimation considering the maximum likelihood and moments approach. An application reveals that the model proposed can be very useful in fitting real data. A final discussion concludes the paper.
En el presente paper se considera una extensión de la distribución exponencial basada en mezclas de distribuciones positivas. Estudiamos las principales propiedades de esta nueva distribución, con especial énfasis en sus momentos, función generadora de momentos, y algunas características relacionadas a estudios de confiabilidad. También se analiza la estimación de parámetros a través de los métodos de momentos y de máxima verosimilitud. Una aplicación muestra que el modelo propuesto puede ser muy útil para ajustar datos reales. Una discusión final concluye el artículo.
https://doi.org/10.15446/rce.v37n1.44355
1Universidade de São Paulo, Instituto de Matematica e Estatística, São Paulo, Brazil. Professor. Email: ymgomez@ime.usp.br
2Universidade de São Paulo, Instituto de Matematica e Estatística, São Paulo, Brazil. Professor. Email: hbolfar@ime.usp.br
3Universidad de Antofagasta, Facultad de Ciencias Básicas, Departamento de Matemáticas, Antofagasta, Chile. Professor. Email: hector.gomez@uantof.cl
The present paper considers an extension of the exponential distribution based on mixtures of positive distributions. We study the main properties of this new distribution, with special emphasis on its moments, moment generator function and some characteristics related to reliability studies. We also discuss parameter estimation considering the maximum likelihood and moments approach. An application reveals that the model proposed can be very useful in fitting real data. A final discussion concludes the paper.
Key words: Exponential distribution, Mixtures of distribution, Likelihood.
En el presente paper se considera una extensión de la distribución exponencial basada en mezclas de distribuciones positivas. Estudiamos las principales propiedades de esta nueva distribución, con especial énfasis en sus momentos, función generadora de momentos, y algunas características relacionadas a estudios de confiabilidad. También se analiza la estimación de parámetros a través de los métodos de momentos y de máxima verosimilitud. Una aplicación muestra que el modelo propuesto puede ser muy útil para ajustar datos reales. Una discusión final concluye el artículo.
Palabras clave: distribución exponencial, mezcla de distribuciones, verosimilitud.
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References
1. Akaike, H. (1974), 'A new look at statistical model identification', IEEE Transaction on Automatic Control AC-19(6), 716-723.
2. Andrews, D. F. & Herzberg, A. M. (1985), Data: A Collection of Problems from Many Fields for the Student and Research Worker, Springer Series in Statistics, New York.
3. Barlow, R. E., Toland, R. H. & Freeman, T. (1984), A Bayesian analysis of stress-rupture life of kevlar 49/epoxy spherical pressure vessels, 'Proc. Conference on Applications of Statistics', Marcel Dekker, New York.
4. Gupta, R. D. & Kundu, D. (1999), 'Generalized exponential distributions', Australian and New Zealand Journal of Statistics 41(2), 173-188.
5. Gupta, R. D. & Kundu, D. (2001), 'Exponentiated exponential family: An alternative to Gamma and Weibull distribution', Biometrical Journal 43(1), 117-130.
6. Marshall, A. W. & Olkin, I. (2007), Life Distributions: Structure of Nonparametric, Semiparametric and Parametric Families, Springer Series in Statistics.
7. Nadarajah, S. & Haghighi, F. (2011), 'An extension of the exponential distribution', Statistics: A Journal of Theoretical and Applied Statistics 45(6), 543-558.
Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX:
@ARTICLE{RCEv37n1a02,
AUTHOR = {Gómez, Yolanda M. and Bolfarine, Heleno and Gómez, Héctor W.},
TITLE = {{A New Extension of the Exponential Distribution}},
JOURNAL = {Revista Colombiana de Estadística},
YEAR = {2014},
volume = {37},
number = {1},
pages = {25-34}
}
References
Akaike, H. (1974), ‘A new look at statistical model identification’, IEEE Transaction on Automatic Control AC-19(6), 716–723.
Andrews, D. F. & Herzberg, A. M. (1985), Data: A Collection of Problems from Many Fields for the Student and Research Worker, Springer Series in Statistics, New York.
Barlow, R. E., Toland, R. H. & Freeman, T. (1984), A Bayesian analysis of stressrupture life of kevlar 49/epoxy spherical pressure vessels, in ‘Proc. Conference on Applications of Statistics’, Marcel Dekker, New York.
Gupta, R. D. & Kundu, D. (1999), ‘Generalized exponential distributions’, Australian and New Zealand Journal of Statistics 41(2), 173–188.
Gupta, R. D. & Kundu, D. (2001), ‘Exponentiated exponential family: An alternative to Gamma and Weibull distribution’, Biometrical Journal 43(1), 117–130.
Marshall, A. W. & Olkin, I. (2007), Life Distributions: Structure of Nonparametric, Semiparametric and Parametric Families.
Nadarajah, S. & Haghighi, F. (2011), ‘An extension of the exponential distribution’, Statistics: A Journal of Theoretical and Applied Statistics 45(6), 543– 558.
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