Journal Published Online: 07 September 2018
Volume 48, Issue 2

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

CODEN: JTEVAB

Abstract

In this article, we make estimation and prediction inferences for the generalized half normal distribution. The maximum likelihood and Bayes estimators of unknown parameters are obtained based on hybrid Type I censored samples. We obtain asymptotic intervals using the observed Fisher information matrix and also construct bootstrap intervals of unknown parameters. Bayes estimators are obtained under the squared error loss function using different approximation methods. We also construct the highest posterior density intervals of unknown parameters. Further one- and two-sample predictors and prediction intervals of censored observations are discussed. A Monte Carlo simulation study is conducted to compare the performance of the proposed methods. We further analyze a real data set for illustrative purposes. Finally, conclusions are presented.

Author Information

Sultana, Farha
Department of Mathematics, Indian Institute of Technology Patna, Bihta, Bihar, India
Tripathi, Yogesh Mani
Department of Mathematics, Indian Institute of Technology Patna, Bihta, Bihar, India
Pages: 24
Price: $25.00
Related
Reprints and Permissions
Reprints and copyright permissions can be requested through the
Copyright Clearance Center
Details
Stock #: JTE20170721
ISSN: 0090-3973
DOI: 10.1520/JTE20170721