On Unified Generalizations of Relative Jensen--Shannon and Arithmetic--Geometric Divergence Measures, and Their Properties
Pranesh Kumar, Inder Jeet Taneja
Abstract
In this paper we shall consider one parametric generalization of some non-symmetric divergence measures. The non-symmetric divergence measures are such as: Kullback-Leibler relative information, χ2-divergence, relative J -- divergence, relative Jensen -- Shannon divergence and relative Arithmetic -- Geometric divergence. All the generalizations considered can be written as particular cases of Csiszár's f-divergence. By putting some conditions on the probability distribution, the aim here is to develop bounds on these measures and their parametric generalizations.
Create a lesson
Related papers
Minimax signal detection in regression under differential privacy
Elly K. H. Hung
A Tetration Distribution
Micah Thornton
Multi-modal Laplace-based sampling
Maxime Egéa, Hanyue Gu, Daniel Rudolf et al.
Studentized inference in randomized experiments when a few units dominate the outcome variation
Xinyuan Chen, Jonathan W. Kiesel, Jonathan R. Woody
Nonparametric Intensity Estimation for Covariate-Driven Poisson Processes Using Deep Learning
Atsutomo Yara, Yoshikazu Terada
Specification LASSO and a Flexible Characteristics-Based Asset Pricing Model
Chaohua Dong, Shuyi Ge, Shaoran Li et al.