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Bayesian one-sided hypothesis testing for shape parameter in half exponential power distribution
Journal of the Korean Data & Information Science Society 2020;31:199-208
Published online January 31, 2020;  https://doi.org/10.7465/jkdi.2020.31.1.199
© 2020 Korean Data and Information Science Society.

Sang Gil Kang1

1Department of Computer and Data Information, Sangji University
Correspondence to: Professor, Department of Computer and Data Information, Sangji University, Wonju 18950, Korea. E-mail: sangkg@sangji.ac.kr
This research was supported by Sangji University Research Fund, 2018.
Received October 4, 2019; Revised October 28, 2019; Accepted October 31, 2019.
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
We consider the one-sided testing for the shape parameter in the half exponential power distribution. Under the noninformative priors such as the reference priors, we develop the objective Bayesian testing methods for the shape parameters. Since the noninformative priors is improper, the Bayes factors can not be computed accurately. Thus we want to develop the Bayesian testing methods via the fractional Bayes factor and the intrinsic Bayes factors to solve this problem. To evaluate the performance of the proposed Bayesian testing methods, we compute the posterior probabilities in some environments of parameters and sample sizes. Thus numerical studies and an example are provided.
Keywords : Fractional Bayes factor, intrinsic Bayes factor, reference prior, shape parameter.