Evaluation of Statistical Forecast Method Efficiency in the Conditions of Dynamic Chaos

Abstract

The current article dedicated to analyzing the feasibility of using conventional techniques of statistical synthesis of prognostic decisions in the conditions of dynamic chaos, which characterizes management in unstable submersion environments. We show the fundamental difference between unstable system state observation series and probabilistic descriptions of traditional models based on the statistical paradigm. We consider an additive model with a chaotic systemic component and non-stationary noise, which describes the aforementioned observation series most adequately. We propose a method for pragmatic estimation of functional efficiency of forecast techniques in the conditions of chaotic non-determinism.