The Reliability Inference for Multicomponent Stress-Strength Model under the Burr X Distribution

被引:0
|
作者
Lio, Yuhlong [1 ]
Chen, Ding-Geng [2 ,3 ]
Tsai, Tzong-Ru [4 ]
Wang, Liang [5 ]
机构
[1] Univ South Dakota, Dept Math Sci, Vermillion, SD 57069 USA
[2] Arizona State Univ, Coll Hlth Solut, Phoenix, AZ 85004 USA
[3] Univ Pretoria, Dept Stat, ZA-0028 Pretoria, South Africa
[4] Tamkang Univ, Dept Stat, New Taipei City 251301, Taiwan
[5] Yunnan Normal Univ, Sch Math, Kunming 650500, Peoples R China
来源
APPLIEDMATH | 2024年 / 4卷 / 01期
基金
新加坡国家研究基金会; 英国医学研究理事会; 中国国家自然科学基金;
关键词
multicomponent stress-strength model; Burr X distribution; maximum likelihood estimation; generalized pivotal estimation; asymptotic theory;
D O I
10.3390/appliedmath4010021
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The reliability of the multicomponent stress-strength system was investigated under the two-parameter Burr X distribution model. Based on the structure of the system, the type II censored sample of strength and random sample of stress were obtained for the study. The maximum likelihood estimators were established by utilizing the type II censored Burr X distributed strength and complete random stress data sets collected from the multicomponent system. Two related approximate confidence intervals were achieved by utilizing the delta method under the asymptotic normal distribution theory and parametric bootstrap procedure. Meanwhile, point and confidence interval estimators based on alternative generalized pivotal quantities were derived. Furthermore, a likelihood ratio test to infer the equality of both scalar parameters is provided. Finally, a practical example is provided for illustration.
引用
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页码:394 / 426
页数:33
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