| fitted.locfit |
Fitted values for a `"locfit"' object.
|
fitted.locfit |
Usage:
fitted(object, data, what="coef", cv=F, studentize=F, type="fit", tr)
Description:
Evaluates the fitted values (i.e. evaluates the surface
at the original data points) for a Locfit object. This function works
by reconstructing the model matrix from the original formula, and
predicting at those points. The function may be fooled; for example,
if the original data frame has changed since the fit, or if the
model formula includes calls to random number generators.
Arguments:
- object
-
"locfit" object.
- data
-
The data frame for the original fit. Usually, this shouldn't be needed,
especially when the function is called directly. It may be needed
when called inside another function.
- what
-
What to compute fitted values of. The default, what="coef", works
with the fitted curve itself. Other choices include "nlx" for the
length of the weight diagram; "infl" for the influence function;
"band" for the bandwidth; "degr" for the local polynomial
degree; "lik" for the maximized local likelihood; "rdf"
for the local residual degrees of freedom and "vari" for the
variance function. The interpolation algorithm for some of these quantities
is questionable.
- cv
-
If TRUE, leave-one-out cross validated fitted values are approximated.
Won't make much sense, unless what="coef".
- studentize
-
If TRUE, residuals are studentized.
- type
-
Type of fit or residuals to compute. The default is "fit" for
fitted.locfit, and "dev" for residuals.locfit.
Other choices include "pear" for Pearson residuals; "raw"
for raw residuals, "ldot" for likelihood derivative;
"d2" for the deviance residual squared; lddot for the
likelihood second derivative. Generally, type should only be
used when what="coef".
- tr
-
Back transformation for likelihood models.
Value:
A numeric vector of the fitted values.
See Also:
locfit,
predict.locfit,
residuals.locfit
Key Words:
smooth
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