Statistical Inference Based on Progressively Type II Censored Data from Weibull Model

被引:7
|
作者
Abu Awwad, Raed R. [1 ]
Raqab, Mohammad Z. [2 ]
Al-Mudahakha, Intesar M. [2 ]
机构
[1] Univ Jordan, Dept Math, Amman, Jordan
[2] Kuwait Univ, Dept Stat & Operat Res, Safat 13060, Kuwait
关键词
Bayes estimation; Bayes prediction; Monte Carlo simulation; Progressive censoring data; Weibull distribution; BAYESIAN-ESTIMATION; ORDER-STATISTICS; PREDICTION; SAMPLES;
D O I
10.1080/03610918.2013.842589
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
In this article, we consider the problem of estimating the shape and scale parameters and predicting the unobserved removed data based on a progressive type II censored sample from the Weibull distribution. Maximum likelihood and Bayesian approaches are used to estimate the scale and shape parameters. The sampling-based method is used to draw Monte Carlo (MC) samples and it has been used to estimate the model parameters and also to predict the removed units in multiple stages of the censored sample. Two real datasets are presented and analyzed for illustrative purposes and Monte carlo simulations are performed to study the behavior of the proposed methods.
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页码:2654 / 2670
页数:17
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