On reconsidering entropies and divergences and their cumulative counterparts: Csiszár's, DPD's and Fisher's type cumulative and survival measures

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL Probability in the Engineering and Informational Sciences Pub Date : 2022-02-21 DOI:10.1017/S0269964822000031
K. Zografos
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引用次数: 1

Abstract

This paper concentrates on the fundamental concepts of entropy, information and divergence to the case where the distribution function and the respective survival function play the central role in their definition. The main aim is to provide an overview of these three categories of measures of information and their cumulative and survival counterparts. It also aims to introduce and discuss Csiszár's type cumulative and survival divergences and the analogous Fisher's type information on the basis of cumulative and survival functions.
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重新考虑熵和散度及其累积对等物:Csiszár’s、DPD’s和Fisher’s型累积和生存度量
本文集中讨论了熵、信息和散度的基本概念,其中分布函数和各自的生存函数在它们的定义中起着中心作用。主要目的是概述这三类信息测量及其累积和生存对应项。并在累积和生存函数的基础上,介绍和讨论Csiszár的类型累积和生存分歧以及类似的Fisher的类型信息。
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来源期刊
CiteScore
2.20
自引率
18.20%
发文量
45
审稿时长
>12 weeks
期刊介绍: The primary focus of the journal is on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, mathematical finance and probabilistic networks and graphs. Papers on analytic properties and related disciplines are also considered, as well as more general papers on applied and computational probability, if appropriate. Readers include academics working in statistics, operations research, computer science, engineering, management science and physical sciences as well as industrial practitioners engaged in telecommunications, computer science, financial engineering, operations research and management science.
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