testdim.multiblock {ade4} | R Documentation |
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), ...)
object |
|
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 |
An object of class krandxval
Stephanie Bougeard (stephanie.bougeard@anses.fr) and Stephane Dray (stephane.dray@univ-lyon1.fr)
Stone M. (1974) Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36, 111-147
mbpcaiv
, mbpls
,
randboot.multiblock
, as.krandxval
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)