Parameter Estimation and Prediction for the Generalized Half Normal Distribution under Progressive Hybrid Censoring

Authors
Farha Sultana 1
Yogesh Tripathi 1
Manoj Kumar Rastogi 2
1 Department of Mathematics, IIT Patna, 810106, India
2 National Institute of Pharmaceutical Education and Research, Hajipur-844102, India
10.29252/jirss.18.1.191
Abstract
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.
Keywords
Bayesian estimates‎
‎HPD intervals‎
‎Maximum likelihood estimates‎
‎Tierney and Kadane method‎
‎Type II progressive hybrid censoring‎
‎Prediction‎
(1) Dr. A. Asgharzadeh, Department of Statistics , University of Mazandaran Babolsar, Iran, Email: akbar548@yahoo.com (2) Dr. Sanku Dey, Department of Statistics, St. Anthony’s College, Shillong-793001, Meghalaya, India, Email: sankud66@gmail.com
Journal of the Iranian Statistical Society
Volume 18, Issue 1
June 2019
Pages 191-236

  • Receive Date 23 July 2022