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Revista Colombiana de Estadística
Print version ISSN 0120-1751
Rev.Colomb.Estad. vol.40 no.2 Bogotá July/Dec. 2017
https://doi.org/10.15446/rce.v40n2.60375
http://dx.doi.org/10.15446/rce.v40n2.60375
1University of Isfahan, Department of Statistics, Isfahan, Iran. PhD. Email: e.zamanzade@sci.ui.ac.ir; ehsanzamanzadeh@yahoo.com
2Hakim Sabzevari University, Department of Statistics, Sabzevar, Iran. PhD. Email: mahdizadeh.m@live.com
In this paper, we develop some goodness of fit tests for Rayleigh distribution based on Phi-divergence. Using Monte Carlo simulation, we compare the power of the proposed tests with some traditional goodness of fit tests including Kolmogorov-Smirnov, Anderson-Darling and Cramer von-Mises tests. The results indicate that the proposed tests perform well as compared with their competing tests in the literature. Finally, the new procedures are illustrated via two real data sets.
Key words: Goodness of fit test, Monte Carlo simulation, Phi-divegence, Rayleigh distribution.
En este artículo desarrollamos pruebas de bondadn de ajuste para distribución Rayleigh basados en divergencia Phi. Usando simulaciones de Monte Carlo, comparamos el poder de las pruebas propuestas con algunas pruebas tradicionales incluyendo Kolmogorov-Smirnov, Anderson-Darling y Cramer von-Mises. Los resultados indican que la prueba propuesta funciona mejor que las otras pruebas reportadas en literatura. Finalmente, los procedimientos nuevos son ilustrados sobre dos conjuntos de datos reales.
Palabras clave: distribución Rayleigh, Divergencia Phi, Pruebas de bondad de ajuste, Simulaciones Monte Carlo.
Texto completo disponible en PDF
References
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Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX:
@ARTICLE{RCEv40n2a05,
AUTHOR = {Zamanzade, Ehsan and Mahdizadeh, M.},
TITLE = {{Goodness of Fit Tests for Rayleigh Distribution Based on Phi-Divergence}},
JOURNAL = {Revista Colombiana de Estadística},
YEAR = {2017},
volume = {40},
number = {2},
pages = {279-290}
}