广义阶统计量p-间隔的似然比比较和对数凸性

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL
Mahdi Alimohammadi, M. Esna-Ashari, J. Navarro
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引用次数: 0

摘要

由于广义阶统计量在统计学的许多分支中的重要性,研究广义阶统计量的随机比较已显示出广泛的兴趣。本文研究了GOS $p$-间距的似然比排序,建立了一些灵活适用的结果。我们还通过提供一些有用的引理来解决一些尚未解决的相关问题。由于我们没有对模型参数施加限制(就像以前的研究那样),我们的研究结果产生了新的结果,用于比较各种有用的有序随机变量模型,包括顺序统计量、顺序顺序统计量、k记录值、Pfeifer记录值以及具有任意审查计划的渐进式ii型审查顺序统计量。并给出了一些关于保持间隔间对数凸性的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Likelihood ratio comparisons and logconvexity properties of p-spacings from generalized order statistics
Due to the importance of generalized order statistics (GOS) in many branches of Statistics, a wide interest has been shown in investigating stochastic comparisons of GOS. In this article, we study the likelihood ratio ordering of $p$-spacings of GOS, establishing some flexible and applicable results. We also settle certain unresolved related problems by providing some useful lemmas. Since we do not impose restrictions on the model parameters (as previous studies did), our findings yield new results for comparison of various useful models of ordered random variables including order statistics, sequential order statistics, $k$-record values, Pfeifer's record values, and progressive Type-II censored order statistics with arbitrary censoring plans. Some results on preservation of logconvexity properties among spacings are provided as well.
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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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