Thanks to Kit Baum, a new package -mlowess- is now
available on SSC.
-mlowess- is for lowess smoothing with multiple predictors.
It follows -fractileplot-, posted recently.
Stata 8 is required.
-mlowess- computes lowess smooths of a response
on specified predictors simultaneously; that is,
each smooth is adjusted for the others. Fitted
values may be saved in new variables. By default,
adjusted values of the response and the lowess
smooth are plotted against each predictor.
The approach is based on methodology for
generalised additive models, but -mlowess- is
primarily intended for exploratory graphics,
rather than model fitting with inferential apparatus.
For example, it might be useful to check whether
predictors are worth including in a model at
all, or as such or transformed.
In my experience the graphics take much longer
than the numerics with -mlowess-. In particular,
-mlowess- is probably best for that and other reasons
for considering models with only a modest number of
predictors.
Nick
[email protected]
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