Optimized Local Regression: Computational Methods for the Moving Average Case

Optimized moving local regression is an extension of Cleveland’s loess technique that takes a suspected misspecification of the model into account. The weights are chosen so that the effect of the misspecification is minimized. The derivation of optimal weights is shown to be similar to that of an optimal design for an experiment.