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.
机构:
Univ Salerno, Dipartimento Matemat, Via Giovanni Paolo II,132, I-84084 Fisciano, ItalyUniv Salerno, Dipartimento Matemat, Via Giovanni Paolo II,132, I-84084 Fisciano, Italy
Capaldo, Marco
Di Crescenzo, Antonio
论文数: 0引用数: 0
h-index: 0
机构:
Univ Salerno, Dipartimento Matemat, Via Giovanni Paolo II,132, I-84084 Fisciano, ItalyUniv Salerno, Dipartimento Matemat, Via Giovanni Paolo II,132, I-84084 Fisciano, Italy
Di Crescenzo, Antonio
Meoli, Alessandra
论文数: 0引用数: 0
h-index: 0
机构:
Univ Salerno, Dipartimento Matemat, Via Giovanni Paolo II,132, I-84084 Fisciano, ItalyUniv Salerno, Dipartimento Matemat, Via Giovanni Paolo II,132, I-84084 Fisciano, Italy