Testing exponentiality based on Kullback-Leibler information with progressively Type-II censored data

被引：74

作者：

Balakrishnan, Narayanaswamy ^{[1
]}

Rad, Arezou Habibi

Arghami, Naser Reza

机构：

[1] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada

[2] Ferdowsi Univ Mashhad, Sch Math Sci, Dept Stat, Mashhad 91775, Iran

来源：

IEEE TRANSACTIONS ON RELIABILITY | 2007年 / 56卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

entropy; hazard function; maximum entropy; Monte Carlo simulation; order statistics; progressively Type-II censored data;

D O I：

10.1109/TR.2007.895308

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We express the joint entropy of progressively censored order statistics in terms of an incomplete integral of the hazard function, and provide a simple estimate of the joint entropy of progressively Type-II censored data. We then construct a goodness-of-fit test statistic based on Kullback-Leibler information with progressively Type-II censored data. Finally, by using Monte Carlo simulations, the power of the test is estimated, and compared against several alternatives under different progressive censoring schemes.

引用

页码：301 / 307

页数：7

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