mathematics//simulation

Simulation executes the rules of a model to produce possible trajectories or observations. It makes assumptions operational: parameters, initial conditions and random inputs jointly determine what the model can produce. Repeated runs can explore variability within those assumptions.

Simulation executes the rules of a model to produce possible trajectories or observations. It makes assumptions operational: parameters, initial conditions and random inputs jointly determine what the model can produce. Repeated runs can explore variability within those assumptions.

Agreement with simulated data demonstrates behaviour inside the generator, not automatically in the world it imitates. Discretization determines how a continuous model becomes computable; synthetic data describes generated observations used for learning and evaluation.