Transitioning away from stochastic process models

Summary: This article introduces a probability approach based on fraction-of-time (FOT) for constructing probabilistic models from individual time series, without the need for the abstraction of a stochastic process. This approach allows for a more practical and accurate description of the properties of time series and avoids the limitations of standard stochastic process models and assumptions of ergodicity.