Parameter inference and model comparison using theoretical predictions from noisy simulations

Understand

When inferring unknown parameters or comparing different models, data must be compared to underlying theory.

• Even if a model has no closed-form solution to derive summary statistics, it is often still possible to simulate mock data in order to generate theoretical predictions.
• For realistic simulations of noisy data, this is identical to drawing realizations of the data from a likelihood distribution.
• Though the estimated summary statistic from simulated data vectors may be unbiased, the estimator has variance which should be accounted for.