Introduction
Certain complex phenomena defy description through deterministic equations. In such cases, random modelling becomes essential, allowing us to statistically analyse the information within the signal. The idea of non-reproducibility of the studied phenomenon roots the concept of randomness; conducting two experiments under identical conditions does not yield identical results. However, we can observe certain similarities—such as trends, fluctuations, and evolutions. We refer to signals characterized by this non-predictability as random, because past knowledge does not ensure error-free future predictions. Random modelling nonetheless enables forecasts with calculable average errors (e.g., temperature predictions).