fdm2id (version 1.0.1)

KERREG: Kernel Regression

Description

This function builds a kernel regression model.

Usage

KERREG(
  x,
  y,
  bandwidth = 1,
  tune = FALSE,
  methodparameters = NULL,
  graph = FALSE,
  seed = NULL,
  ...
)

Value

The classification model, as an object of class model-class.

Arguments

x

Predictor matrix.

y

Response vector.

bandwidth

The bandwidth parameter.

tune

If true, the function returns parameters instead of a classification model.

methodparameters

Present for interface consistency with performance (which always passes it when fitting a model). Currently unused: KERREG does not support reusing pre-tuned parameters.

graph

Present for interface consistency with performance (which always passes it when fitting a model). Currently unused: KERREG does not produce a plot.

seed

A specified seed for random number generation, so that two runs on the same data give the same model. Every learning method accepts it, so that it can be set the same way whatever the method; the deterministic ones simply have nothing to draw and give the same model with or without it.

...

Other parameters.

See Also

npregress

Examples

require (datasets)
data (trees)
KERREG (trees [, -3], trees [, 3])