Ordering and aging properties of systems with dependent components governed by the Archimedean copula

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL
T. Sahoo, Nil Kamal Hazra
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引用次数: 1

Abstract

Abstract Copula is one of the widely used techniques to describe the dependency structure between components of a system. Among all existing copulas, the family of Archimedean copulas is the popular one due to its wide range of capturing the dependency structures. In this paper, we consider the systems that are formed by dependent and identically distributed components, where the dependency structures are described by Archimedean copulas. We study some stochastic comparisons results for series, parallel, and general $r$-out-of-$n$ systems. Furthermore, we investigate whether a system of used components performs better than a used system with respect to different stochastic orders. Furthermore, some aging properties of these systems have been studied. Finally, some numerical examples are given to illustrate the proposed results.
由阿基米德联结控制的依赖成分系统的有序和老化性质
Copula是一种广泛使用的描述系统组件间依赖结构的技术。在所有现存的copulas中,阿基米德copulas家族因其广泛捕获依赖结构而受到欢迎。在本文中,我们考虑由依赖和同分布的组件组成的系统,其中依赖结构由阿基米德copula描述。研究了串联、并联和一般r -out-of- n系统的一些随机比较结果。此外,我们还研究了在不同的随机阶数下,一个由废旧部件组成的系统是否比一个废旧部件组成的系统性能更好。此外,还研究了这些体系的一些老化性能。最后,给出了一些数值算例来说明所提出的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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