Goodness-of-fit test for exponentiality based on Kullback-Leibler information

被引：34

作者：

Choi, B ^{[1
]}

Kim, K ^{[1
]}

Song, SH ^{[1
]}

机构：

[1] Korea Univ, Dept Stat, Seoul 136701, South Korea

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2004年 / 33卷 / 02期

关键词：

exponential distribution; Kullback-Leibler information; goodness-of-fit; Shannon's entropy; entropy estimator; power analysis;

D O I：

10.1081/SAC-120037250

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, we discuss goodness-of-fit tests of the exponential distribution based on Kullback-Leibler information. To construct test statistics, Van Es' and Correa's entropy estimator are used as an estimator of Shannon's entropy. Critical values for various sample sizes determined by means of Monte Carlo simulations are presented for each of test statistics. Also, formulas for calculating approximate critical values for given sample sizes are provided for the respective test statistics. A Monte Carlo power analysis is performed for various alternatives and sample sizes in order to compare the proposed tests with several existing goodness-of-fit tests based on the empirical distribution function (EDF). Simulation results show that Kullback-Leibler information tests have higher powers than the EDF tests.

引用

页码：525 / 536

页数：12

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