cv.cggd {cggd}R Documentation

Computes K-fold cross-validated error curve for cggd

Description

Computes the K-fold cross-validated mean squared prediction error for cggd.

Usage

cv.cggd(x, y, nfolds = 6, kmax=40 , 
           trace = FALSE, plot.it = TRUE, se=TRUE, ...)

Arguments

x Input to cggd
y Input to cggd
nfolds Number of folds
kmax Max number of iterations per model
trace Show computations
plot.it Plot it
se Include standard error bands
... Additional arguments to cggd

Value

cv The CV loss curve at each value of k
cv.error The standard error of the CV curve

Author(s)

Cun-Hui Zhang and Ofer Melnik

References

Cun-Hui Zhang (2007) "Continuous Generalized Gradient Descent" Journal of Computational and Graphical Statistics ; see also http://stat.rutgers.edu/~cunhui/software/CGGD.html.

Examples

data(Wine)
attach(Wine)
cv.cggd(x.learning,y.learning,kmax=40,fctr=1e3)
detach(Wine)

[Package cggd version 0.8 Index]