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Entropy 2017, 19(5), 208; doi:10.3390/e19050208

Objective Bayesian Entropy Inference for Two-Parameter Logistic Distribution Using Upper Record Values

1
Department of Statistics, Daejeon University, Daejeon 34520, Korea
2
Department of Statistics, Kyungpook National University, Daegu 41566, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Kevin H. Knuth
Received: 24 March 2017 / Revised: 28 April 2017 / Accepted: 29 April 2017 / Published: 3 May 2017
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Abstract

In this paper, we provide an entropy inference method that is based on an objective Bayesian approach for upper record values having a two-parameter logistic distribution. We derive the entropy that is based on the i-th upper record value and the joint entropy that is based on the upper record values. Moreover, we examine their properties. For objective Bayesian analysis, we obtain objective priors, namely, the Jeffreys and reference priors, for the unknown parameters of the logistic distribution. The priors are based on upper record values. Then, we develop an entropy inference method that is based on these objective priors. In real data analysis, we assess the quality of the proposed models under the objective priors and compare them with the model under the informative prior. View Full-Text
Keywords: entropy; logistic distribution; objective Bayesian analysis; upper record value entropy; logistic distribution; objective Bayesian analysis; upper record value
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Seo, J.I.; Kim, Y. Objective Bayesian Entropy Inference for Two-Parameter Logistic Distribution Using Upper Record Values. Entropy 2017, 19, 208.

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