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

Year 2020, Volume: 49 Issue: 6, 2119 - 2133, 08.12.2020

Farzana Noor , Ahthasham Sajid Maha Ghazal İmranullah Khan Mehwish Zaman İmran Baig

https://doi.org/10.15672/hujms.635684

Cited By: 1

Abstract

In this article, Maximum likelihood estimation (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 (SELF), precautionary loss function (PLF) and K-loss function (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

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