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Published in:
2015 | OriginalPaper | Chapter
23. Bayesian Weighted Information Measures
Author : Salimeh Yasaei Sekeh
Published in: Interdisciplinary Bayesian Statistics
Publisher: Springer International Publishing
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Abstract
Following Ebrahimi et al. (J Stat Res Iran 3:113–137, 2006), we study weighted information measure in univariate case. In particular, we address the concept of comparison models based on information measure and, in our case, specially Kullback–Leibler discrimination measure. The main result is presenting the relationship of weighted mutual information measure and weighted entropy. Indeed, the importance of Weibull distribution family in weighted Kullback–Leibler information and Kullback–Leibler information has been carefully examined, which is useful in comparison models. As a notable application of the result, we study normal distributions, which can prove the expected motivation.