In this work, we derive a family of maximum second order entropy distributions provided

that the mean and the Gini index are known as the optional side conditions. Then via these

distributions, families of ...

and inequality measures constraints. Next, we consider a generalization of Gini index and based on the principle of maximum-entropy we find the probability distribution that maximizes the entropy among all probability distributions supported on non-negative real...

on copula entropy and dependence. The principle

of maximum entropy provides a method to select the unknown pdf

(or pmf) compatible to entropy under a specified constraint. This idea

was introduced by Jaynes 1957 and obtained with a...

Generalisations of maximum entropy principle (MEP) and minimum

discrimination information principle (MDIP) are described by Kapur and

Kesavan (1989) . In this paper, we used generalised entropies and replaced

Shannon entropy...

In this paper, we use cumulative residual Kullback-Leibler information (CRKL) and cumulative Kullback-Leibler information (CKL) to construct two goodness-offit test statisttics for testing exponentiality with progressively ...

In this paper, at first we derive a family of maximum Tsallis

entropy distributions under optional side conditions on the mean income

and the Gini index. Furthermore, corresponding with these distributions

a ...

Maximizing the Shannon entropy and Renyi entropy in a class of distributions subject to a set of constraints are the topics that play an important role in statistical inference. In this paper some distributions with maximum ...

Using the maximum entropy principle with Tsallis entropy, some distribution families for modeling income distribution are obtained. By considering income inequality measures,maximum Tsallis entropy distributions under the constraint on generalized...