It seems that in general
gam(y~lo(x)) # gam() from the gam package.
and
loess(y~x)
give slightly different results (in respect of the predicted/fitted
values).
Most noticeable at the endpoints of the range of x.
Can anyone enlighten me about the reason for this difference?
Is it possible to twiddle the control parameters, for either or both
functions,
so as to obtain identical results?
Thanks.
cheers,
Rolf Turner
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