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Akbar Asgharzadeh

Akbar Asgharzadeh

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty of Mathematical Sciences
Address: Department of Statistics University of Mazandaran Babolsar, IRAN
Phone: 011-54302476

Research

Title
Multicomponent Stress-strength Reliability with Exponentiated Teissier Distribution
Type
JournalPaper
Keywords
multicomponent stress-strength reliability, exponentiated Teissier distribution, Bayes estimation
Year
2022
Journal Austrian Journal of Statistics
DOI
Researchers Hossein Pasha Zanoosi ، Ahmad Pourdarvish ، Akbar Asgharzadeh

Abstract

This article deals with the problem of reliability in a multicomponent stress-strength (MSS) model when both stress and strength variables are from exponentiated Teissier (ET) distributions. The reliability of the system is determined using both classical and Bayesian methods, based on two scenarios where the common scale parameter is unknown or known. In the first scenario, where the common scale parameter is unknown, the maximum likelihood estimation (MLE) and the approximate Bayes estimation are derived. In the second scenario, where the scale parameter is known, the MLE, the uniformly minimum variance unbiased estimator (UMVUE) and the exact Bayes estimation are obtained. In the both scenarios, the asymptotic confidence interval and the highest probability density credible interval are established. Furthermore, two other asymptotic confidence intervals are computed based on the Logit and Arcsin transformations. Monte Carlo simulations are implemented to compare the different proposed methods. Finally, one real example is presented in support of suggested procedures