涉及残余熵和过去熵的进一步结果及其应用

IF 0.9 4区数学 Q3 STATISTICS & PROBABILITY Statistics & Probability Letters Pub Date : 2024-07-07 DOI:10.1016/j.spl.2024.110201

Mohamed Kayid

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引用次数: 0

摘要

在本文中，我们研究了残余熵和过去熵的一些随机方面。然后，我们将研究结果应用于阶次统计、相干系统和记录值。我们介绍了残余熵和过去熵的非参数估计器，并使用模拟数据集和真实数据集说明了它们的性能。

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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Further results involving residual and past extropy with their applications

In this paper we have investigated some stochastic aspects of residual extropy and past extropy. We then apply the results to the context of order statistics, coherent systems and record values. Nonparametric estimators for residual extropy and past extropy were introduced and their performance was illustrated using simulated data sets and real data sets.

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来源期刊

Statistics & Probability Letters 数学-统计学与概率论

CiteScore

1.60

自引率

0.00%

发文量

173

审稿时长

6 months

期刊介绍： Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature. Statistics & Probability Letters is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission. The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of Statistics & Probability Letters is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability. The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published.

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