Cubic transmuted (CT) distributions were introduced recently by Granzotto et al. (2017). In this article, we derive Shannon entropy, Gini's mean difference and Fisher information (matrix) for CT distributions and establish some of their theoretical properties. In addition, we propose cubic transmuted Shannon entropy and cubic transmuted Gini's mean difference. The CT Shannon entropy is expressed in terms of Kullback-Leibler divergences, while the CT Gini's mean difference is shown to be connected with energy distances. We show that the Kullback-Leibler and Chi-square divergences are free of the underlying parent distribution.
翻译:Granzotto等人(2017年)最近引入了立体变换(CT)分布。在本篇文章中,我们从香农变异(Shanon entropy,Gini的平均值差异)和渔业信息(Matrix)中得出CT分布,并确定了它们的理论属性。此外,我们提议了立体变异(Channon entropy)和立方变异(Gini)的平均值差异。CT 香农变异(CHon Channon entropy)以Kullback- Leiber 和 Chi- sequarre 的平均值差异表示,而CT Gini的平均值差异则显示与能源距离有关。我们表明Kullback- Leiber 和 Chi- sequar 差异与父系分布无关。