Title : ( Goodness of fit test using Lin-Wong divergence based on Type-I censored data )
Authors: ALIREZA PAKGOHAR , Arezou Habibirad , F. Yousefzadeh ,
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Abstract
Goodness of ft tests with two different methods are carried out in the present paper in order to recognize normal and exponential distributions within Type-I censored data. Here, we use the Lin-Wong divergence as our proposed measure of distance between distributions and compare its performance with that of other well known distance measures using an empirical distribution function and Shannon entropy concept. Furthermore, we present two real data analysis procedures using those proposed methods.
Keywords
, Anderson, Darling; Crame´r, von Mises; Exponentiality; Kernel Density; Kolmogorov, Smirnov; Kullback, Leibler; Normality.
@article{paperid:1071091,
author = {PAKGOHAR, ALIREZA and Habibirad, Arezou and },
title = {Goodness of fit test using Lin-Wong divergence based on Type-I censored data},
journal = {Communications in Statistics Part B: Simulation and Computation},
year = {2018},
month = {December},
issn = {0361-0918},
pages = {1--21},
numpages = {20},
keywords = {Anderson-Darling; Crame´r-von Mises; Exponentiality; Kernel Density;
Kolmogorov-Smirnov; Kullback-Leibler; Normality.},
}
%0 Journal Article
%T Goodness of fit test using Lin-Wong divergence based on Type-I censored data
%A PAKGOHAR, ALIREZA
%A Habibirad, Arezou
%A
%J Communications in Statistics Part B: Simulation and Computation
%@ 0361-0918
%D 2018
