Classical and Bayesian Inference of an Exponentiated Half-Logistic Distribution under Adaptive Type II Progressive Censoring

Entropy

Wenhao Gui¹  Ziyu Xiong¹ 

[1] Department of Mathematics, Beijing Jiaotong University, Beijing 100044, China;

关键词: adaptive type-II progressive censoring;    exponentiated half-logistic distribution;    maximum likelihood estimation;    Bayesian estimation;    importance sampling;    Lindley method;   

DOI  :  10.3390/e23121558

来源: DOAJ

【 摘 要 】

The point and interval estimations for the unknown parameters of an exponentiated half-logistic distribution based on adaptive type II progressive censoring are obtained in this article. At the beginning, the maximum likelihood estimators are derived. Afterward, the observed and expected Fisher’s information matrix are obtained to construct the asymptotic confidence intervals. Meanwhile, the percentile bootstrap method and the bootstrap-t method are put forward for the establishment of confidence intervals. With respect to Bayesian estimation, the Lindley method is used under three different loss functions. The importance sampling method is also applied to calculate Bayesian estimates and construct corresponding highest posterior density (HPD) credible intervals. Finally, numerous simulation studies are conducted on the basis of Markov Chain Monte Carlo (MCMC) samples to contrast the performance of the estimations, and an authentic data set is analyzed for exemplifying intention.

【 授权许可】

Unknown