Statistical inference of the stress-strength reliability for inverse Weibull distribution under an adaptive progressive type-II censored sample
AIMS MATHEMATICS(2023)
摘要
In this paper, we investigate classical and Bayesian estimation of stress-strength reliability delta = P(X > Y) under an adaptive progressive type-II censored sample. Assume that X and Y are independent random variables that follow inverse Weibull distribution with the same shape but different scale parameters. In classical estimation, the maximum likelihood estimator and asymptotic confidence interval are deduced. An approximate maximum likelihood estimator approach is used to obtain the explicit form. In Bayesian estimation, the Bayesian estimators are derived based on symmetric entropy loss function and LINEX loss function. Due to the complexity of integrals, we proposed Lindley's approximation to get the approximate Bayesian estimates. To compare the different estimators, we performed Monte Carlo simulations. Under gamma prior, the approximate maximum likelihood estimator performs better than Bayesian estimators. Under non-informative prior, the approximate maximum likelihood estimator has the same behavior as Bayesian estimators. In the end, two data sets are used to prove the effectiveness of the proposed methods.
更多查看译文
关键词
approximate maximum likelihood estimation,Bayesian estimation,inverse Weibull distribution,stress-strength reliability
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要