On cumulative residual information generating function: properties, inference and applications

被引:1
作者
Chakraborty, Siddhartha [1 ]
Pradhan, Biswabrata [1 ]
机构
[1] Indian Stat Inst, SQC & OR Unit, 203 BT Rd, Kolkata 700108, India
关键词
Asymptotic normality; Empirical distribution function; Generalized cumulative residual entropy; Hypothesis testing; Mixed systems; Copula; Stochastic order; ENTROPY; COHERENT;
D O I
10.1007/s12597-024-00754-4
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We consider a new information generating function introduced by Kharazmi and Balakrishnan (Commun Stat Theory Methods 52(15):5260-5273, 2023), called cumulative residual information generating (CRIG) function and study some new properties. Also we find that the CRIG function has a relationship with many popular measures like Gini's mean difference, cumulative residual Tsallis entropy and cumulative residual extropy. We obtain numerous bounds for CRIG function and study characterization in terms of CRIG of first order statistic. We propose two non-parametric estimators of CRIG function and investigate their asymptotic properties. Based on one of the proposed estimators, a new test statistic for testing equality of two distribution functions is developed. Finally, CRIG function for mixed systems is analyzed and complexity of systems is studied.
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页数:21
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