Estimation of the system reliability for generalized inverse Lindley distribution based on different sampling designs

被引:8
|
作者
Akgul, Fatma Gul [1 ]
Yu, Keming [2 ]
Senoglu, Birdal [3 ]
机构
[1] Artvin Coruh Univ, Dept Comp Engn, TR-08000 Artvin, Turkey
[2] Brunel Univ, Dept Math Sci, London, England
[3] Ankara Univ, Dept Stat, Ankara, Turkey
关键词
Stress-strength reliability; sampling designs; maximum likelihood; imperfect ranking; efficiency; MAXIMUM-LIKELIHOOD ESTIMATORS; STRESS-STRENGTH RELIABILITY; PARAMETER;
D O I
10.1080/03610926.2019.1705977
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
In this paper, we are interested in estimating stress-strength reliability when the distributions of stress and strength are independent generalized inverse Lindley (GIL) under different sampling designs, namely, simple random sampling (SRS), ranked set sampling (RSS) and percentile ranked set sampling (PRSS). In the context of parameter estimation, we use maximum likelihood (ML) methodology. The performance of the ML estimators of stress-strength reliability based on SRS, RSS and PRSS are compared via a Monte-Carlo simulation study for different parameter settings and sample sizes under the assumptions of perfect and imperfect ranking, respectively. At the end of the study, the insulin resistance data set is analyzed to implement the proposed methodologies.
引用
收藏
页码:1532 / 1546
页数:15
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