Estimating the parameter of the exponentiated half-logistic distribution under generalized type II hybrid censoring scheme†
Kyeongjun Lee1
1Department of Mathematics and Big Data Science, Kumoh National Institute of Technology
Correspondence to: † This research was supported by Kumoh National Institute of Technology (2022).
1 Assistant professor, Department of Mathematics and Big Data Science, Kumoh National Institute of Technology, Gyeongbuk 39177, Korea. E-mail: indra_74@naver.com
1 Assistant professor, Department of Mathematics and Big Data Science, Kumoh National Institute of Technology, Gyeongbuk 39177, Korea. E-mail: indra_74@naver.com
Received August 31, 2023; Revised September 19, 2023; Accepted September 19, 2023.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Abstract
- In this paper, we consider the parameter for the exponentiated half logistic distribution (ExHfLg) when data are generalized type II hybrid censored (GenTy2HC) samples. The parameter for the ExHfLg is estimated by the Bayesian method. We consider conjugate priors (gamman and quasi prior) and corresponding posterior distributions are obtained. We also obtain the maximum likelihood estimator (MLE) of the parameter under the GenTy2HC samples. We compare the proposed estimators in the terms of the mean square error and bias. Finally, a real data set has been analysed for illustrative purpose.
- Keywords : Bayesian estimation, exponentiated half-logistic distribution, gamma and quasi prior distributions, generalized type II hybrid censoring, half-logistic distribution, maximum likelihood estimation, squared error and Linex loss functions
Full Text(PDF) Free
