Separable processes

Separable processes are a type of mathematical model used to analyze how random events change over space and time. They simplify complex data by breaking down a two-dimensional process into the product of two separate one-dimensional processes—one for space and one for time—making it easier to study and predict patterns. This approach helps statisticians and scientists understand phenomena like temperature variations or climate data across different locations and periods without getting overwhelmed by the full complexity of their interactions.