Hi,
I'm wondering if anyone is aware of any R packages that do kernel
smoothing with at least 4 predictors. The dataset I'm working with now
has 4 predictors, and I can fit a loess smooth, but loess has the
disadvantage that it can produce fitted values outside the range of the
response-something a kernel smoother can't do. All the packages I've
found so far work for 2 or fewer predictors.
If anyone's aware of an R package for kernel smoothing that will work
with at least 4 predictors, please let me know.
Thanks,
Paul Louisell
[EMAIL PROTECTED]
ARPC
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