Stress-Strength Analysis of Inverse Weibull Model Using Type-II Progressive Hybrid Censoring and Its Application to Light-Emitting Diodes | ||||
مجلة البØÙˆØ« التجارية | ||||
Article 29, Volume 47, Issue 1, January 2025, Page 120-166 PDF (3.08 MB) | ||||
Document Type: تجاریة کل ما یتعلق بالعلوم التجاریة | ||||
DOI: 10.21608/zcom.2024.325769.1386 | ||||
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Authors | ||||
سارة Ù…ØÙ…د عبدالعليم ![]() | ||||
1قسم Ø§Ù„Ø¥ØØµØ§Ø¡ ØŒ كلية التجارة ØŒ جامعة الزقازيق | ||||
2قسم Ø§Ù„Ø¥ØØµØ§Ø¡ والرياضة والتأمين، کلية التجارة، جامعة الزقازيق، مصر | ||||
Abstract | ||||
In this paper, we discuss the estimation of δ = P(Y < X) based on Type-II progressive hybrid censored samples when X and Y are two independent Inverse Weibull distributions with different scale parameters, but having the same shape parameter. Different methods for estimating δ are applied. The maximum likelihood estimator and the The observed Fisher information matrix is computed and it is used to construct an asymptotic confidence interval for δ. Bayes estimate of δ under the assumptions of independent gamma priors. Markov Chain Monte Carlo (MCMC) technique is used for Bayes computation. Moreover, by using the MCMC method, we achieve the highest posterior density ( HPD) credible intervals. Monte Carlo simulations are performed to compare the efficiency of the proposed estimators. One data analysis has been presented for illustrative purposes. Keywords: Stress-strength model, Inverse Weibull distribution, maximum likelihood estimator, Bayes estimator, Markov Chain Monte Carlo,, Type-II progressively hybrid censoring. | ||||
Keywords | ||||
Stress-strength model; Inverse Weibull distribution; maximum likelihood estimator; Bayes estimator; Markov Chain Monte Carlo | ||||
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