locfit.robust implements a robust local regression where
outliers are iteratively identified and downweighted, similarly
to the lowess method (Cleveland, 1979). The iterations and scale
estimation are performed on a global basis.The scale estimate is 6 times the median absolute residual, while the robust downweighting uses the bisquare function. These are performed in the S code so easily changed.
This can be interpreted as an extension of M estimation to local
regression. An alternative extension (implemented in locfit via
family="qrgauss") performs the iteration and scale estimation
on a local basis.
locfit.robust(x, y, weights, ..., iter=3)locfit model formula or a numeric vector
of the predictor variable.x is numeric, y gives the response variable.locfit.raw."locfit" object.locfit,
locfit.raw