testdim.multiblock function

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

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

## 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

Returns

An object of class krandxval

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")

Author(s)

Stéphanie Bougeard (stephanie.bougeard@anses.fr ) and Stéphane Dray (stephane.dray@univ-lyon1.fr )

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)