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fitted.locfit

Fitted values for a ‘"locfit"’ object.

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.

Usage

## S3 method for class 'locfit'
fitted(object, data=NULL, what="coef", cv=FALSE,
studentize=FALSE, type="fit", tr, ...)

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.

...

arguments passed to and from methods.

Value

A numeric vector of the fitted values.

See Also

locfit, predict.locfit, residuals.locfit

locfit

Local Regression, Likelihood and Density Estimation

v1.5-9.4
GPL (>= 2)
Authors
Catherine Loader [aut], Jiayang Sun [ctb], Lucent Technologies [cph], Andy Liaw [cre]
Initial release
2020-03-24

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