Residual
Also: prediction error
The difference between an observed value and a model's prediction.
Residual structure versus time, input, or state reveals bias, missing dynamics, correlation, or changed conditions.
- Formula
r[k] = y_measured[k] − y_predicted[k]
Example Residuals growing with speed suggest the model missed a speed-dependent effect.
Common misconception Small training residuals do not establish predictive validity on new data.