Bayesian and Non–Bayesian Estimation for Two Generalized Exponential Populations Under Joint Type II Censored Scheme

Samir Kamel Ashour, Osama Eraki Abo-Kasem

Abstract


In this paper, Bayesian and non-Bayesian estimators have been obtained for two generalized exponential populations under joint type II censored scheme, which generalize results of Balakrishnan and Rasouli (2008) and Shafay et al. (2013). The maximum likelihood estimators (MLEs) of the parameters and Bayes estimators have been developed under squared error loss function as well as under LINEX loss function. Moreover, approximate confidence region are also discussed and compared with two Bootstrap confidence regions. Also the MLE and three confidence intervals for the stress–strength parameter  are explored. A numerical illustration for these new results is given. 

Keywords


Generalized exponential distribution; joint type-II censoring; maximum likelihood estimation; Confidence bounds; Bootstrap intervals; Coverage probabilities; Bayesian estimation; squared-error loss; linear-exponential loss; stress–strength reliability.

Full Text:

PDF


DOI: http://dx.doi.org/10.18187/pjsor.v10i1.710

Refbacks

  • There are currently no refbacks.




Copyright (c)

Title

Bayesian and Non–Bayesian Estimation for Two Generalized Exponential Populations Under Joint Type II Censored Scheme

Keywords

Generalized exponential distribution; joint type-II censoring; maximum likelihood estimation; Confidence bounds; Bootstrap intervals; Coverage probabilities; Bayesian estimation; squared-error loss; linear-exponential loss; stress–strength reliability.

Description

In this paper, Bayesian and non-Bayesian estimators have been obtained for two generalized exponential populations under joint type II censored scheme, which generalize results of Balakrishnan and Rasouli (2008) and Shafay et al. (2013). The maximum likelihood estimators (MLEs) of the parameters and Bayes estimators have been developed under squared error loss function as well as under LINEX loss function. Moreover, approximate confidence region are also discussed and compared with two Bootstrap confidence regions. Also the MLE and three confidence intervals for the stress–strength parameter  are explored. A numerical illustration for these new results is given. 

Date

2014-05-26

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 10 No. 1, 2014



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810