Classification of Generalized Weighted Cross-entropic Models for Discrete Probability Distribution in Vague Setting
Abstract
The ambiguity of a novel class of generalized weighted cross-entropy models based on discrete probability distributions is the main topic of this paper. A well-known constrained symmetrization of the Kullback-Leibler cross-entropy, the Jensen-Shannon divergence does not require matching support for probability densities. This paper is novel in that it derives a vector-skew Jensen-Shannon divergence by obtaining different cross-entropies for different values of a prevalent scalar A, determining the concavity of the measure with respect to that scalar, and introducing a vector-skew generalization of it.
Fields of Study & Subjects
Statistical Mechanics and Entropy
Mathematical Inequalities and Applications
Probability and Statistical Research
Publication details
- Journal / source
- Asian Journal of Probability and Statistics
- Volume
- 28
- Issue
- 2
- Pages
- 1–9
- Publication date
- 5 February 2026
- Language
- EN