Selection of the number of dimension by two-fold cross-validation for multiblock methods

Description

Function to perform a two-fold cross-validation to select the optimal number of dimensions of multiblock methods, i.e., multiblock principal component analysis with instrumental Variables or multiblock partial least squares

Usage

1
2
## S3 method for class 'multiblock'
testdim(object, nrepet = 100, quantiles = c(0.25, 0.75), ...)

Arguments

object

an object of class multiblock created by mbpls or mbpcaiv

nrepet

integer indicating the number of repetitions

quantiles

a vector indicating the lower and upper quantiles to compute

...

other arguments to be passed to methods

Value

An object of class krandxval

Author(s)

Stephanie Bougeard (stephanie.bougeard@anses.fr) and Stephane 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

See Also

mbpcaiv, mbpls, randboot.multiblock, as.krandxval

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
data(chickenk)
Mortality <- chickenk[[1]]
dudiY.chick <- dudi.pca(Mortality, center = TRUE, scale = TRUE, scannf =
FALSE)
ktabX.chick <- ktab.list.df(chickenk[2:5])
resmbpcaiv.chick <- mbpcaiv(dudiY.chick, ktabX.chick, scale = TRUE,
option = "uniform", scannf = FALSE)
## nrepet should be higher for a real analysis
test <- testdim(resmbpcaiv.chick, nrepet = 10)
test
if(adegraphicsLoaded())
plot(test)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.