locfit: cpplot – R documentation

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cpplot

Compute a Cp plot.

Description

The cpplot function loops through calls to the cp function (and hence to link{locfit}), using a different smoothing parameter for each call. The returned structure contains the Cp statistic for each fit, and can be used to produce an AIC plot.

Usage

cpplot(..., alpha, sig2)

Arguments

`...`	arguments to the `cp`, `locfit` functions.
`alpha`	Matrix of smoothing parameters. The `cpplot` function loops through calls to `cp`, using each row of `alpha` as the smoothing parameter in turn. If `alpha` is provided as a vector, it will be converted to a one-column matrix, thus interpreting each component as a nearest neighbor smoothing parameter.
`sig2`	Residual variance. If not specified, the residual variance is computed using the fitted model with the fewest residual degrees of freedom.

Value

An object with class "gcvplot", containing the smoothing parameters and CP scores. The actual plot is produced using plot.gcvplot.

Examples

data(ethanol)
plot(cpplot(NOx~E,data=ethanol,alpha=seq(0.2,1.0,by=0.05)))

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