Open AccessGoodness of fit tests for Rayleigh distribution based on Phi-divergence
Author(s) -
M. Mahdizadeh,
Ehsan Zamanzade
Publication year - 2017
Publication title -
revista colombiana de estadística/revista colombiana de estadistica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.256
H-Index - 16
eISSN - 2389-8976
pISSN - 0120-1751
DOI - 10.15446/rce.v40n2.60375
Subject(s) - goodness of fit , rayleigh distribution , divergence (linguistics) , mathematics , monte carlo method , statistics , kolmogorov–smirnov test , anderson–darling test , set (abstract data type) , statistical physics , statistical hypothesis testing , computer science , probability density function , physics , philosophy , linguistics , programming language
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 proposed procedures are illustrated via a real data set.