Kernel-based estimation of P(X > Y) in ranked set sampling

被引：0

作者：

Mahdizadeh, M. ^{[1
]}

Zamanzade, Ehsan ^{[2
]}

机构：

[1] Hakim Sabzevari Univ, Dept Stat, POB 397, Sabzevar, Iran

[2] Univ Isfahan, Dept Stat, Esfahan 8174673441, Iran

来源：

SORT-STATISTICS AND OPERATIONS RESEARCH TRANSACTIONS | 2016年 / 40卷 / 02期

关键词：

Bandwidth selection; Judgment ranking; Stress-strength model; CROSS-VALIDATION;

D O I：

暂无

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

This article is directed at the problem of reliability estimation using ranked set sampling. A non parametric estimator based on kernel density estimation is developed. The estimator is shown to be superior to its analog in simple random sampling. Monte Carlo simulations are employed to assess performance of the proposed estimator. Two real data sets are analysed for illustration.

引用

页码：243 / 265

页数：23

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Kernel-based estimation of P(X &gt; Y) in ranked set sampling

Kernel-based estimation of P(X > Y) in ranked set sampling