cv.cggd {cggd} | R Documentation |
Computes the K-fold cross-validated mean squared prediction error for cggd.
cv.cggd(x, y, nfolds = 6, kmax=40 , trace = FALSE, plot.it = TRUE, se=TRUE, ...)
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 |
cv |
The CV loss curve at each value of k |
cv.error |
The standard error of the CV curve |
Cun-Hui Zhang and Ofer Melnik
Cun-Hui Zhang (2007) "Continuous Generalized Gradient Descent" Journal of Computational and Graphical Statistics ; see also http://stat.rutgers.edu/~cunhui/software/CGGD.html.
data(Wine) attach(Wine) cv.cggd(x.learning,y.learning,kmax=40,fctr=1e3) detach(Wine)