Estimation Based on Progressive First-Failure Censored Sampling with Binomial Removals

Ahmed A. Soliman; Ahmed H. Abd Ellah; Nasser A. Abou-Elheggag; Rashad M. El-Sagheer

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Estimation Based on Progressive First-Failure Censored Sampling with Binomial Removals

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摘要

In this paper, the inference for the Burr-X model under progressively first-failure censoring scheme is discussed. Based on this new censoring were the number of units removed at each failure time has a discrete binomial distribution. The maximum likelihood, Bootstrap and Bayes estimates for the Burr-X distribution are obtained. The Bayes estimators are obtained using both the symmetric and asymmetric loss functions. Approximate confidence interval and highest posterior density interval (HPDI) are discussed. A numerical example is provided to illustrate the proposed estimation methods developed here. The maximum likelihood and the different Bayes estimates are compared via a Monte Carlo simulation study.

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《智能信息管理（英文）》 |2013年第4期|117-125|共9页
作者
Ahmed A. Soliman; Ahmed H. Abd Ellah; Nasser A. Abou-Elheggag; Rashad M. El-Sagheer;
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作者单位

Faculty of Science;

Islamic University;

Madinah;

Saudi Arabia;

Mathematics Department;

Faculty of Science;

Al-Azhar University;

Nasr-City;

Cairo;

Egypt;

Mathematics Department;

Sohag University;

Sohag;

Egypt;

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原文格式 PDF
正文语种 chi
中图分类数学;
关键词
Burr-X; Distribution; Progressive; First-Failure; Censored; Bayesian; and; Non-Bayesian; Estimations; Loss; Function; Bootstrap; Random; Removals;

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Estimation Based on Progressive First-Failure Censored Sampling with Binomial Removals

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