基于订单统计外熵的不准确性动态残差测量

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL
M. Mohammadi, M. Hashempour, O. Kamari
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引用次数: 0

摘要

在本文中,我们介绍了一种利用熵概念量化阶次统计剩余误差的新方法。我们探讨了这种新度量的各种属性和特征。此外,我们还将有序随机变量的不准确性概念扩展为动态版本,并证明这种动态信息度量可提供分布函数的唯一确定性。此外,我们还通过分析一阶统计的残余不准确性来研究特定的寿命分布。我们建议对所提出的度量进行非参数核估计。仿真结果表明,使用交叉验证法选择带宽的核估计器性能最佳。最后,还介绍了所提测量方法在模型选择中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the dynamic residual measure of inaccuracy based on extropy in order statistics

In this paper, we introduce a novel way to quantify the remaining inaccuracy of order statistics by utilizing the concept of extropy. We explore various properties and characteristics of this new measure. Additionally, we expand the notion of inaccuracy for ordered random variables to a dynamic version and demonstrate that this dynamic information measure provides a unique determination of the distribution function. Moreover, we investigate specific lifetime distributions by analyzing the residual inaccuracy of the first-order statistics. Nonparametric kernel estimation of the proposed measure is suggested. Simulation results show that the kernel estimator with bandwidth selection using the cross-validation method has the best performance. Finally, an application of the proposed measure on the model selection is provided.

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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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