Cumulative and relative cumulative residual information generating measures and associated properties

被引:5
|
作者
Kharazmi, Omid [1 ]
Balakrishnan, Narayanaswamy [2 ]
机构
[1] Vali E Asr Univ Rafsanjan, Fac Math Sci, Dept Stat, Rafsanjan, Iran
[2] McMaster Univ, Dept Math & Stat, Hamilton, ON, Canada
关键词
Information generating function; Jensen-information generating function; Jensen-Shannon entropy; survival function; Jensen-Gini mean difference; Kullback-Leibler divergence; SHANNON; GINI;
D O I
10.1080/03610926.2021.2005100
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 work, we propose cumulative residual information generating (CRIG) and relative cumulative residual information generating (RCRIG) measures and then establish some of their properties. A new divergence measure based on the CRIG function is proposed to measure the closeness between two survival functions as well as a cumulative residual Kullback-Leibler divergence. We also present Jensen-cumulative residual information generating function, whose derivatives generate some new cumulative information measures such as Jensen-cumulative residual Taneja entropy, Jensen-fractional cumulative residual entropy and Jensen-Gini mean difference measure. We further show that the Jensen-cumulative residual information generating function can be expressed as a mixture of two versions of the proposed new divergence measure.
引用
下载
收藏
页码:5260 / 5273
页数:14
相关论文
共 50 条