Bayesian and Non-Bayesian Estimation for the Bivariate Inverse Weibull Distribution Under Progressive Type-II Censoring

被引：0

作者：

Muhammed H.Z. ^{[1
]}

Almetwally E.M. ^{[2
]}

机构：

[1] Department of Mathematical Statistics, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza

[2] Department of Statistics, Faculty of Business Administration, Delta University of Science and Technology, Mansoura

来源：

Annals of Data Science | 2023年 / 10卷 / 02期

关键词：

Bayesian estimation; Bivariate inverse Weibull distribution; Bootstrap confidence Intervals; Maximum likelihood estimation; Prior distribution; Progressive Type-II censoring;

D O I：

10.1007/s40745-020-00316-7

中图分类号：

学科分类号：

摘要：

Recently, bivariate inverse Weibull distribution was derived; many of its properties have been discussed. Progressive Type-II censoring for bivariate inverse Weibull distribution has been proposed. The problem of estimating the unknown parameters of this distribution in the presence of progressive Type-II censoring by both Maximum likelihood and Bayesian estimation methods is considered in this paper. Moreover, asymptotic and bootstrap confidence intervals for the model parameters are obtained. Simulation study and a real data set are presented to illustrate the proposed procedure. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

引用

页码：481 / 512

页数：31

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