Affiliation:
1. Faculty of Technology and Development, Zagazig University, Zagazig 44519, Egypt
2. Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
Abstract
A new two-parameter extended exponential lifetime distribution with an increasing failure rate called the Poisson–exponential (PE) model was explored. In the reliability experiments, an adaptive progressively Type-II hybrid censoring strategy is presented to improve the statistical analysis efficiency and reduce the entire test duration on a life-testing experiment. To benefit from this mechanism, this paper sought to infer the unknown parameters, as well as the reliability and failure rate function of the PE distribution using both the likelihood and product of spacings estimation procedures as a conventional view. For each unknown parameter, from both classical approaches, an approximate confidence interval based on Fisher’s information was also created. Additionally, in the Bayesian paradigm, the given classical approaches were extended to Bayes’ continuous theorem to develop the Bayes (or credible interval) estimates of the same unknown quantities. Employing the squared error loss, the Bayesian inference was developed based on independent gamma assumptions. Because of the complex nature of the posterior density, the Markov chain with the Monte Carlo methodology was used to obtain data from the whole conditional distributions and, therefore, evaluate the acquired Bayes point/interval estimates. Via extensive numerical comparisons, the performance of the estimates provided was evaluated with respect to various criteria. Among different competing progressive mechanisms, using four optimality criteria, the best censoring was suggested. Two real chemical engineering datasets were also analyzed to highlight the applicability of the acquired point and interval estimators in an actual practical scenario.
Funder
Princess Nourah bint Abdulrahman University Researchers Supporting Project
Subject
Geometry and Topology,Logic,Mathematical Physics,Algebra and Number Theory,Analysis
Reference37 articles.
1. The Poisson–exponential lifetime distribution;Cancho;Comput. Stat. Data Anal.,2011
2. The Poisson–exponential distribution: A Bayesian approach;Cancho;J. Appl. Stat.,2011
3. Estimation for the parameter of Poisson–exponential distribution under Bayesian paradigm;Singh;J. Data Sci.,2014
4. Poisson–exponential distribution: Different methods of estimation;Rodrigues;J. Appl. Stat.,2018
5. Reliability estimation for Poisson-Exponential model under progressive Type-II censoring data with binomial removal data;Kumar;Statistica,2016
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献