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randxval

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)

References

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

See Also

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)

ade4

Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

v1.7-16
GPL (>= 2)
Authors
Stéphane Dray <stephane.dray@univ-lyon1.fr>, Anne-Béatrice Dufour <anne-beatrice.dufour@univ-lyon1.fr>, and Jean Thioulouse <jean.thioulouse@univ-lyon1.fr>, with contributions from Thibaut Jombart, Sandrine Pavoine, Jean R. Lobry, Sébastien Ollier, Daniel Borcard, Pierre Legendre, Stéphanie Bougeard and Aurélie Siberchicot. Based on earlier work by Daniel Chessel.
Initial release

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