Transitioning away from stochastic process models

It has been over 30 years since a paradigm shift from abstract stochastic process models to more concrete Fraction-of-Time Probability models for time-series data was called for and was supported by this journal's editor in chief. Yet, little, if any, detectable progress in making this transition has occurred. This paper reviews this needed transition and attempts to facilitate it with a new type of stochastic process model. The primary purpose of this model is to serve as a pedagogical tool for facilitating the conceptual transition from the standard relatively abstract way of thinking to a more concrete alternative. The utility of this parsimonious alternative was thoroughly proven when it was introduced in an advanced 1987 textbook, and the evidence in support has continued to accumulate in subsequent theoretical and applied research publications. But resistance to change is ever present.

Automated summary

This paper reviews the necessary transition from abstract stochastic process models to more concrete Fraction-of-Time Probability models for time-series data. It introduces a new type of stochastic process model as a pedagogical tool to facilitate the conceptual transition. Despite accumulating evidence in support, resistance to change remains a challenge.