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ade4 (version 1.7-5)

randboot.multiblock: Bootstraped simulations for multiblock methods

Description

Function to perform bootstraped simulations for multiblock principal component analysis with instrumental variables or multiblock partial least squares, in order to get confidence intervals for some parameters, i.e., regression coefficients, variable and block importances

Usage

"randboot"(object, nrepet = 199, optdim, ...)

Arguments

object
an object of class multiblock created by mbpls or mbpcaiv
nrepet
integer indicating the number of repetitions
optdim
integer indicating the optimal number of dimensions, i.e., the optimal number of global components to be introduced in the model
...
other arguments to be passed to methods

Value

krandboot

References

Carpenter, J. and Bithell, J. (2000) Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians.Statistics in medicine, 19, 1141-1164

See Also

mbpcaiv, mbpls, testdim.multiblock, as.krandboot

Examples

Run this code
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, nf = 4)
## nrepet should be higher for a real analysis
test <- randboot(resmbpcaiv.chick, optdim = 4, nrepet = 10)
test
if(adegraphicsLoaded())
plot(test$bipc) 

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