Parameters estimation of Burr-XII distribution under first-failure progressively unified hybrid censoring schemes

被引：3
|
作者：
Jia, Jun-mei [1 ]
Yan, Zai-zai [1 ]
Peng, Xiu-yun [1 ]
机构：
[1] Inner Mongolia Univ Technol, Coll Sci, Hohhot 010051, Peoples R China
来源：
STATISTICAL ANALYSIS AND DATA MINING | 2018年 / 11卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Bayes estimation; bootstrap confidence interval; Burr-XII distribution; first-failure progressively unified hybrid censoring; maximum likelihood estimation;
D O I：
10.1002/sam.11391
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a new life test plan called a first-failure progressively unified hybrid censoring scheme is introduced. Based on this type of censoring scheme, we obtain the maximum likelihood and the Bayes estimators of the unknown parameters from the Burr-XII distribution. The asymptotic confidence intervals, two kinds of bootstrap confidence intervals and highest posterior density credible intervals of the unknown parameters are constructed. Analysis of a real data set is present to demonstrate the application of the proposed method. The performances of the point and interval estimations are compared by using a Monte Carlo simulation study.
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页码：271 / 281
页数：11
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