The locfit
function computes a local fit at a selected set
of points (as defined by the ev
argument). The predict.locfit
function is used to interpolate from these points to any other points.
The method is based on cubic hermite polynomial interpolation, using the
estimates and local slopes at each fit point.
The motivation for this twostep procedure is computational speed.
Depending on the sample size, dimension and fitting procedure, the
local fitting method can be expensive, and it is desirable to keep the
number of points at which the direct fit is computed to a minimum.
The interpolation method used by predict.locfit()
is usually
much faster, and can be computed at larger numbers of points.
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object 
Fitted object from 
newdata 
Points to predict at. Can be given in several forms: vector/matrix; list, data frame. 
se.fit 
If 
where, what, band 
arguments passed on to

... 
Additional arguments to 
If se.fit=F
, a numeric vector of predictors.
If se.fit=T
, a list with components fit
, se.fit
and
residual.scale
.
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