On progressively censored inverted exponentiated Rayleigh distribution. Issue 3 (11th February 2019)

• Record Type: Journal Article
• Authors: Maurya, Raj Kamal; Tripathi, Yogesh Mani; Sen, Tanmay; Rastogi, Manoj Kumar
• Is Part Of: Journal of statistical computation and simulation. Volume 89:Issue 3(2019)
• Page Start: 492
• Page End: 518
• Publication Date: 2019-02-11
• Subjects: Progressive censoring -- Bayes estimate -- maximum likelihood estimate -- predictive estimate -- prediction interval -- optimum censoring; 62 F10 -- 62 N01 -- 62 N02; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2018.1558225
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: In this paper, we discuss a progressively censored inverted exponentiated Rayleigh distribution. Estimation of unknown parameters is considered under progressive censoring using maximum likelihood and Bayesian approaches. Bayes estimators of unknown parameters are derived with respect to different symmetric and asymmetric loss functions using gamma prior distributions. An importance sampling procedure is taken into consideration for deriving these estimates. Further highest posterior density intervals for unknown parameters are constructed and for comparison purposes bootstrap intervals are also obtained. Prediction of future observations is studied in one- and two-sample situations from classical and Bayesian viewpoint. We further establish optimum censoring schemes using Bayesian approach. Finally, we conduct a simulation study to compare the performance of proposed methods and analyse two real data sets for illustration purposes.