locfit (version 1.1-3)

predict.locfit: Prediction from a Locfit object.

Description

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 two-step 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.

Usage

## S3 method for class 'locfit':
predict(object, newdata, where="fitp", se.fit=FALSE,
               band="none", what="coef", ...)

Arguments

object

Fitted object from locfit().

newdata

Points to predict at. Can be given in several forms: vector/matrix; list, data frame.

where

An alternative to newdata. Choices include "grid" for the grid lfmarg(object); "data" for the original data points and "fitp" for the direct fitting po

se.fit

If TRUE, standard errors are computed along with the fitted values.

band

Compute standard errors for the fit and include confidence bands on the returned object. Default is "none". Other choices include "global" for bands using a global variance estimate; "local" for bands using a l

what

What to compute predicted 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; "ban

...

Additional arguments to preplot.locfit.

Value

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

Examples

data(ethanol)
fit <- locfit(NOx~E,data=ethanol)
predict(fit,c(0.6,0.8,1.0))