Figure 2

Convergence criterion for minimization algorithm. The set of model predictions in data space form a surface known as the model manifold. By comparing the angle between the tangent plane to the Model Manifold and the vector of unfit data, we can monitor convergence to a local minimum of the cost. If αis approximately a right angle, then we are likely near a local minimum. Fits separated by more than $\left|\mathbf{r}\right(\theta \left)\right|cos\alpha$ are likely to correspond to different minima.