ade4 (version 1.7-19)

testdim.multiblock: 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

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

Value

An object of class krandxval

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

Author

Stéphanie Bougeard () and Stéphane Dray ()

References

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

Bougeard, S. and Dray S. (2018) Supervised Multiblock Analysis in R with the ade4 Package. Journal of Statistical Software, 86 (1), 1-17. tools:::Rd_expr_doi("10.18637/jss.v086.i01")

See Also

mbpcaiv, mbpls, randboot.multiblock, as.krandxval

Examples

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)