Semi-automatic selection of summary statistics for ABC model choice

Understand

A central statistical goal is to choose between alternative explanatory models of data.

• In many modern applications, such as population genetics, it is not possible to apply standard methods based on evaluating the likelihood functions of the models, as these are numerically intractable.
• Approximate Bayesian computation (ABC) is a commonly used alternative for such situations.
• ABC simulates data x for many parameter values under each model, which is compared to the observed data xobs.