Bayesian estimation of Rayleigh distribution in the presence of outliers using progressive censoring

Authors : Farzana NOOR, Ahthasham SAJİD, Maha GHAZAL, İmranullah KHAN, Mehwish ZAMAN, İmran BAİG

Pages : 2119-2133

Doi:10.15672/hujms.635684

View : 15 | Download : 7

Publication Date : 2020-12-08

Article Type : Research Paper

Abstract :In this article, Maximum likelihood estimation insert ignore into journalissuearticles values(MLE); and Bayesian estimation for Rayleigh distribution using progressive type-II censoring in the presence of outliers is considered. Inverse Gamma prior and Jeffreys prior are used for Bayesian estimation. Squared error loss function insert ignore into journalissuearticles values(SELF);, precautionary loss function insert ignore into journalissuearticles values(PLF); and K-loss function insert ignore into journalissuearticles values(KLF); are used for obtaining the expressions of Bayes estimators and posterior risks. Credible intervals are also derived. A simulation study is presented to discuss the behavior of Bayes estimators. Applicability of the undertaken study is highlighted using three real data sets.
Keywords : Rayleigh distribution, outliers, progressive type II censoring, life testing experiments, prior distribution, loss function