# On generalized entropy measures and pathways

## TL;DR

This paper explores generalized entropy measures, their mathematical properties, and their applications to pathway models, emphasizing the importance of non-additivity in statistical mechanics and connecting to measures of inaccuracy.

## Contribution

It introduces and examines properties of generalized entropies, including Mathai's entropy, and links them to pathway models and differential equations.

## Key findings

- Shannon entropy's logarithmic form leads to additivity under product probability.
- Mathai's generalized entropy can produce exponential and power law behaviors.
- Connections are established between Mathai's entropy and Kerridge's measure of inaccuracy.

## Abstract

Product probability property, known in the literature as statistical independence, is examined first. Then generalized entropies are introduced, all of which give generalizations to Shannon entropy. It is shown that the nature of the recursivity postulate automatically determines the logarithmic functional form for Shannon entropy. Due to the logarithmic nature, Shannon entropy naturally gives rise to additivity, when applied to situations having product probability property. It is argued that the natural process is non-additivity, important, for example, in statistical mechanics, even in product probability property situations and additivity can hold due to the involvement of a recursivity postulate leading to a logarithmic function. Generalizations, including Mathai's generalized entropy are introduced and some of the properties are examined. Situations are examined where Mathai's entropy leads to pathway models, exponential and power law behavior and related differential equations. Connection of Mathai's entropy to Kerridge's measure of "inaccuracy" is also explored.