The LOESS Procedure

Iterative Reweighting

PROC LOESS can do iterative reweighting to improve the robustness of the fit in the presence of outliers in the data. Iterative reweighting is also appropriate when statistical inference is requested and the error distribution is symmetric but not Gaussian.

The number of iterations is specified by the ITERATIONS= option in the MODEL statement. The default is ITERATIONS=1, which corresponds to no reweighting.

At iterations beyond the first iteration, the local weights $w_ i$ of the previous section are replaced by $r_ i w_ i$, where $r_ i$ is a weight that decreases as the residual of the fitted value at the previous iteration at the point corresponding to $d_ i$ increases. See Cleveland and Grosse (1991) and Cleveland, Grosse, and Shyu (1992) for details.