Weighted cumulative residual Kullback-Leibler divergence: properties and applications

被引：2

作者：

Chakraborty, Siddhartha ^{[1
]}

Pradhan, Biswabrata ^{[1
]}

机构：

[1] Indian Stat Inst, SQC & OR Unit, 203 BT Rd, Kolkata 700108, India

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2024年 / 53卷 / 07期

关键词：

Weighted cumulative Kullback-Leibler divergence; Weighted mean residual lifetime; Goodness-of-fit test; Type-I censoring; Type-II censoring; GOODNESS-OF-FIT; INFORMATION; ENTROPY;

D O I：

10.1080/03610918.2022.2108053

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：

Weighted cumulative residual Kullback-Leibler information measure and its dynamic version are proposed and their properties are investigated. Also weighted cumulative Kullback-Leibler information measure along with its dynamic version is introduced. Monotonicity properties of the dynamic information measures are studied. A goodness-of-fit test is developed for exponential distribution using weighted cumulative residual Kullback-Leibler information measure based on complete and censored data. It is observed that proposed tests perform well for monotone decreasing hazard alternatives under censored data. Four data sets are analyzed for illustration.

引用

页码：3541 / 3553

页数：13

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