R: Two-fold cross-validation

randxval {ade4}

R Documentation

Two-fold cross-validation

Description

Functions and classes to manage outputs of two-fold cross-validation for one (class randxval) or several (class krandxval) statistics

Usage

as.krandxval(RMSEc, RMSEv, quantiles = c(0.25, 0.75), names =
colnames(RMSEc), call = match.call())
## S3 method for class 'krandxval'
print(x, ...)
as.randxval(RMSEc, RMSEv, quantiles = c(0.25, 0.75), call =
match.call())
## S3 method for class 'randxval'
print(x, ...)

Arguments

`RMSEc`	a vector (class `randxval`) or a matrix (class `krandxval`) with the root-mean-square error of calibration (statistics as columns and repetions as rows)
`RMSEv`	a vector (class `randxval`) or a matrix (class `krandxval`) with the root-mean-square error of validation (statistics as columns and repetions as rows)
`quantiles`	a vector indicating the lower and upper quantiles to compute
`names`	a vector of names for the statistics
`call`	the matching call
`x`	an object of class `randxval` or `krandxval`
`...`	other arguments to be passed to methods

Value

an object of class randxval or krandxval

Author(s)

St\'ephane Dray (stephane.dray@univ-lyon1.fr)

References

Stone M. (1974) Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36, 111-147

Examples

## an example corresponding to 10 statistics and 100 repetitions
cv <- as.krandxval(RMSEc = matrix(rnorm(1000), nrow = 100), RMSEv =
matrix(rnorm(1000, mean = 1), nrow = 100))
cv
if(adegraphicsLoaded())
plot(cv)

[Package ade4 version 1.7-4 Index]