Inference for constant-stress Weibull competing risks model under generalized progressive hybrid censoring

被引:0
|
作者
Wang, Liang [1 ]
Tripathi, Yogesh Mani [2 ]
Lodhi, Chandrakant [2 ]
Zuo, Xuanjia [1 ]
机构
[1] Yunnan Normal Univ, Sch Math, Kunming, Yunnan, Peoples R China
[2] Indian Inst Technol Patna, Dept Math, Bihta, India
基金
中国国家自然科学基金;
关键词
Accelerated life test; Competing risks model; Weibull distribution; Generalized progressive hybrid censoring; Maximum likelihood estimation; Likelihood ratio test; ACCELERATED LIFE-TEST; EXACT LIKELIHOOD INFERENCE; TESTS; DESIGN; PLANS;
D O I
10.1016/j.matcom.2021.08.017
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, accelerated life test is considered when the latent failure times follow Weibull competing risks models. When both scale and shape parameters are nonconstant and affected by operating stress, inference is discussed for a constant-stress model under a generalized progressive hybrid censoring. Maximum likelihood estimates together with existence and uniqueness are established, and the approximate confidence intervals for unknown parameters are proposed based on the asymptotic theory. Further, when the distributions of failure causes have common shape or scale parameters, associated point and interval estimates are also proposed. In addition, to compare the equivalence of the parameters of different Weibull competing risks, likelihood ratio tests for interested hypotheses are presented for complementary. Finally, extensive numerical studies and a real-life example are provided for illustrations. (C) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
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页码:70 / 83
页数:14
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