Model calibration

Model calibration is the process of adjusting unknown model parameters so that model outputs agree with selected observations according to a defined fitting criterion.

Calibration workflow

Specify the observations, observation model, parameters to estimate, initial conditions and fitting objective. Then solve or simulate the model repeatedly while searching the parameter space.

Avoiding circular evaluation

Agreement with the calibration data shows that the model can reproduce the information used to fit it. It is not independent evidence of predictive performance.

Diagnostics

Residual patterns, parameter uncertainty, identifiability and sensitivity should be examined rather than reporting only the best-fitting curve.