Properties of the Shannon, Rényi and other entropies: dependence in parameters, robustness in distributions and extremes
Iryna Bodnarchuk, Yuliya Mishura, Kostiantyn Ralchenko
Abstract
We calculate and analyze various entropy measures and their properties for selected probability distributions. The entropies considered include Shannon, Rényi, generalized Rényi, Tsallis, Sharma-Mittal, and modified Shannon entropy, along with the Kullback-Leibler divergence. These measures are examined for several distributions, including gamma, chi-squared, exponential, Laplace, and log-normal distributions. We investigate the dependence of the entropy on the parameters of the respective distribution. We also study the convergence of Shannon entropy for certain probability distributions. Furthermore, we identify the extreme values of Shannon entropy for Gaussian vectors.