异构尺度变量的最大阶统计量的MRL排序

IF 1.2 4区 数学 Q2 STATISTICS & PROBABILITY
Abedin Haidari, M. Sattari, Ghobad Saadat Kia (Barmalzan), N. Balakrishnan
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引用次数: 1

摘要

为了比较独立异构非负尺度变量在平均剩余寿命阶上的最大阶统计量,引入了一个新的框架。这个框架可以看作是众所周知的多离群值尺度模型的推广,它还包括所有随机变量都是异质的情况。我们还找到了在平均剩余生命阶上比较具有完全异质尺度参数和具有齐质尺度参数的最大阶统计量的一些充分条件。作为得到结果的例子,给出了广义伽玛分布、第二类广义beta分布、幂广义威布尔分布和半正态分布。这项工作的发现概括并加强了这一方向上的一些现有结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MRL ordering of largest order statistics from heterogeneous scale variables
ABSTRACT For comparing largest order statistics from independent heterogeneous non-negative scale variables in the mean residual life order, a new framework is introduced here. This framework can be viewed as a generalization of the well-known multiple-outlier scale model, and it additionally includes the situation in which all the random variables are heterogeneous. We also find some sufficient conditions for comparing the largest order statistics, one with complete heterogeneous scale parameters and another with homogeneous scale parameters, in the mean residual life order. As examples of the obtained results, generalized gamma, generalized beta of the second kind, power-generalized Weibull, and half-normal distributions are all presented. The findings of this work generalize and also reinforce some of the existing results in this direction.
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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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