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]