期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：13
页码：3526-3539
出版社：Journal of Theoretical and Applied
摘要：R�nyi entropy is the important concept developed by R�nyi in the context of entropy theory. We study in detail this measure of information in case of multivariate skew normal Cauchy distributions. Mixture model of these distributions is proposed. In addition, upper and lower bounds of entropy both types Shannon and R�nyi are found on this model. Also, an asymptotic expression for R�nyi entropy for a mixture of skew distributions is given in approximation by using some inequalities, multinomial theorem and properties of L^p -spaces. Finally, we give a real data examples to illustrate the behavior of R�nyi entropy of the proposed mixture model.
