Exact inference for joint Type-I hybrid censoring model with exponential competing risks data

被引：1

作者：

Mao, Song ^{[1
]}

Shi, Yi-min ^{[2
]}

Wang, Xiao-lin ^{[3
]}

机构：

[1] Shanxi Univ, Dept Econ & Management, Taiyuan 030006, Shanxi, Peoples R China

[2] Northwestern Polytech Univ, Dept Appl Math, Xian 710072, Shaanxi, Peoples R China

[3] 78020 Unit, Kunming 655000, Yunnan, Peoples R China

来源：

ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES | 2017年 / 33卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Joint Type-I hybrid censoring; Competing causes; Moment generating function; Likelihood inference; Bootstrap methods; EXACT LIKELIHOOD INFERENCE; STEP-STRESS MODEL; FAILURE; POPULATIONS;

D O I：

10.1007/s10255-017-0688-8

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Assuming that the failure time under different risk factors follows the independent exponential distribution, a joint model under Type-I hybrid censoring is addressed in detail. Based on the Maximum likelihood estimates (MLEs) of unknown parameters, we obtain exact distributions of MLEs by using the moment generating function (MGF). Confidence intervals (CIs) of parameters are constructed through both the exact method and the parametric bootstrap method. Then we compare the performances of different methods by Monte Carlo simulations. Finally, the validity of the proposed models and methods are demonstrated by a numerical example.

引用

页码：645 / 658

页数：14

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