Volume 18, Issue 1 (6-2019)                   JIRSS 2019, 18(1): 191-236 | Back to browse issues page


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Sultana F, Tripathi Y, Kumar Rastogi M. Parameter Estimation and Prediction for the Generalized Half Normal Distribution under Progressive Hybrid Censoring. JIRSS. 2019; 18 (1) :191-236
URL: http://jirss.irstat.ir/article-1-492-en.html
Department of Mathematics, IIT Patna, 810106, India , yogesh@iitp.ac.in
Abstract:   (738 Views)
In this paper, the problem of estimating unknown parameters of a generalized half- normal distribution is considered under Type II progressive hybrid censoring which is a combination of Type II progressive and hybrid censoring schemes. We obtain maximum likelihood estimators of parameters and also construct asymptotic intervals using the observed Fisher information matrix. Further Bayes estimates are computed under the squared error loss function by applying different approximation methods. We also obtain prediction estimates and prediction intervals of censored observations. The performance of different methods is compared using Monte Carlo simulations and a real data set is analyzed for illustrative purposes.
Full-Text [PDF 146 kb]   (76 Downloads)    
Type of Study: Original Paper | Subject: 62Nxx: Survival analysis and censored data
Received: 2018/01/22 | Accepted: 2018/09/16 | Published: 2018/11/27

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