Nonlinear Dynamics for the prediction of Statistical Distributions: An Operational Research perspective

Abstract

A semantic connection between nonlinear or linear dynamical systems and statistical Gaussian distributions is developed as a theory. This connection is applied to predict changes in the Gaussian distribution when models of a complexsystem are available for making decisions in any operational research framework. A typical real case is considered in the analysis and the application of the theory is explained. As a theoretical extension, modified confidence intervals and extended hypothesis testing related to inferential statistics are briefly discussed to consider the global impact of this developed tool.