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:: Volume 16, Issue 1 (9-2022) ::
JSS 2022, 16(1): 209-238 Back to browse issues page
Statistical Inference of Two-Parameter Weibull Distribution under Progressive Type-II Censoring with Random Removals
Masumeh Ghahramani‎ , Maryam Sharafi * , Reza Hashemi
Abstract:   (1310 Views)

One of the most critical challenges in progressively Type-II censored data is determining the removal plan. It can be fixed or random so that is chosen according to a discrete probability distribution. Firstly, this paper introduces two discrete joint distributions for random removals, where the lifetimes follow the two-parameter Weibull distribution. The proposed scenarios are based on the normalized spacings of exponential progressively Type-II censored order statistics. The expected total test time has been obtained under the proposed approaches. The parameters estimation are derived using different estimation procedures as the maximum likelihood, maximum product spacing and least-squares methods. Next, the proposed random removal schemes are compared to the discrete uniform, the binomial, and fixed removal schemes via a Monte Carlo simulation study in terms of their biases; root means squared errors of estimators and their expected experiment times. The expected experiment time ratio is also discussed under progressive Type-II censoring to the complete sampling plan. 

Keywords: Expected Experiment Time, Lifetime Data, Maximum Likelihood Estimation, Maximum Product Spacing Estimation, Random Removal.
Full-Text [PDF 368 kb]   (481 Downloads)    
Type of Study: Research | Subject: Reliability
Received: 2021/06/6 | Accepted: 2022/09/1 | Published: 2022/08/2
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Ghahramani‎ M, Sharafi M, Hashemi R. Statistical Inference of Two-Parameter Weibull Distribution under Progressive Type-II Censoring with Random Removals. JSS 2022; 16 (1) :209-238
URL: http://jss.irstat.ir/article-1-771-en.html


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Volume 16, Issue 1 (9-2022) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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