Non-parametric predictive inference for future order statistics

被引：7

作者：

Coolen, Frank P. A. ^{[1
]}

Coolen-Maturi, Tahani ^{[2
]}

Alqifari, Hana N. ^{[3
]}

机构：

[1] Univ Durham, Dept Math Sci, Durham DH1 3LE, England

[2] Univ Durham, Sch Business, Durham, England

[3] Qassim Univ, Dept Math, Buraydah, Saudi Arabia

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2018年 / 47卷 / 10期

关键词：

Future order statistics; Lower and upper probabilities; Multiple comparisons; Non-parametric predictive inference; Pairwise comparisons; INTERVALS;

D O I：

10.1080/03610926.2017.1342834

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This article presents non-parametric predictive inference for future order statistics. Given the data consisting of n real-valued observations, m future observations are considered and predictive probabilities are presented for the rth-ordered future observation. In addition, joint and conditional probabilities for events involving multiple future order statistics are presented. The article further presents the use of such predictive probabilities for order statistics in statistical inference, in particular considering pairwise and multiple comparisons based on two or more independent groups of data.

引用

页码：2527 / 2548

页数：22

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