Stochastic comparisons of second-order statistics from dependent and heterogenous modified proportional hazard rate observations

IF 1.2 4区 数学 Q2 STATISTICS & PROBABILITY Statistics Pub Date : 2023-03-04 DOI:10.1080/02331888.2023.2177999
Rongfang Yan, Jiale Niu
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引用次数: 0

Abstract

This manuscript studies the stochastic comparisons of the second-order statistics from dependent or independent and heterogeneous modified proportional hazard rate observations. Some sufficient conditions on the usual stochastic order of the second-order statistics from dependent and heterogeneous observations are established under Archimedean copula. Some sufficient conditions are also provided in the hazard rate order of the second-order statistics arising from two sets of independent and heterogeneous or multiple-outlier modified proportional hazard rate observations. Some numerical examples are given to illustrate the theoretical findings.
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依赖和异质修正比例危险率观测的二阶统计量的随机比较
本文研究了依赖或独立和异质修正比例危险率观测的二阶统计量的随机比较。在阿基米德copula下,建立了依赖和异质观测的二阶统计量通常随机有序的一些充分条件。本文还给出了由两组独立的、异质的或多离群值修正的比例风险率观测值所产生的二阶统计量的风险率顺序的一些充分条件。给出了一些数值算例来说明理论结果。
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来源期刊
Statistics
Statistics 数学-统计学与概率论
CiteScore
1.00
自引率
0.00%
发文量
59
审稿时长
12 months
期刊介绍: Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
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