Point and interval estimation under progressive type-I interval censoring with random removal

被引：3
|
作者：
Budhiraja, Sonal [1 ]
Pradhan, Biswabrata [1 ]
机构：
[1] Indian Stat Inst, SQC & OR Unit, 203 BT Rd, Kolkata 700108, India
来源：
STATISTICAL PAPERS | 2020年 / 61卷 / 01期
关键词：
Asymptotic normality; Binomial removal; Consistency; Maximum likelihood estimator; Regularity condition; Tolerance interval; GENERALIZED EXPONENTIAL-DISTRIBUTION; MAXIMUM-LIKELIHOOD-ESTIMATION; TOLERANCE LIMITS; WEIBULL DISTRIBUTION; CONFIDENCE; PREDICTION; INFERENCE; SAMPLES;
D O I：
10.1007/s00362-017-0948-y
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：
This work considers point and interval estimation based on data from a life test under progressive type-I interval censoring with random removal. The asymptotic properties of the maximum likelihood estimators (MLEs) are established under appropriate regularity conditions. Asymptotic confidence intervals and beta-content gamma-level tolerance interval are obtained by using the asymptotic normality of MLEs. A simulation study is undertaken to assess the performance of the MLEs, confidence intervals and tolerance interval. Lastly, the minimum sample size required to achieve a desired beta-content gamma-level tolerance interval is determined.
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页码：445 / 477
页数：33
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