A Probability Density for Modeling Unknown Physical Processes

TL;DR

This paper introduces a new probability density function designed to model physical processes with unknown mechanisms, offering properties not available in traditional Gaussian or classic densities, especially useful in chaotic physics analysis.

Contribution

It proposes a novel probability density with unique properties tailored for modeling unknown physical processes, filling a gap in existing statistical methods.

Findings

The density has desirable mathematical properties.

It is applicable to chaotic phenomena in physics.

It outperforms traditional densities in modeling unknown processes.

Abstract

This brief paper develops a probability density that models processes for which the physical mechanism is unknown. It has desirable properties which are not realized by densities derived from Gaussian process or other classic methods. In many areas of physics, such the analysis of chaotic phenomena, there is need for a density that has these properties.