Information entropy of the generalized beta distribution

Author:

Polosin Vitaly G.

Abstract

The output distribution of statistical variables characterizes the level of uncertainty of a complex system, the state of which is given by probabilistic changes in internal relationships. Information entropy is an effective tool for analysing the distribution of data in complex systems. Subfamilies of generalized beta distributions of the first and second types includes many simple distributions as special cases. These subfamilies are often used to model the output state of the system by distributions of random variables. There are conditions in the paper, that are imposed on the parameters of the generalized beta distribution to obtain relationships with simpler types. The paper contains an expression for calculating the information entropy, the generalized beta distribution, which includes distributions of the first and second kind as special cases. Expressions of information entropies for the most famous subfamilies of generalized beta distribution also are given.

Publisher

EDP Sciences

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