Usage:

cpplot(..., alpha, sig2)

Description:

The cpplot function loops through calls to the cp function (and hence to linklocfit), 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.

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)))

See Also:

locfit, locfit.raw, gcv, aic, plot.gcvplot

Key Words:

locfit