Definition of Term: Model Discrepancy

No matter how careful a particular model of a real system has been formulated, there will always be a difference between reality, represented by the system value \(y\), and the simulator output \(f(x)\) for any valid input \(x\). The difference \(d=y-f(x^+)\), where \(\strut{x}^+\) is the best input, is referred to as the model discrepancy, which should be incorporated into our analysis in order to make valid statements about the real system. In particular, model discrepancy is vital for procedures such as calibration, history matching and prediction for the real system.