bootsPLS (version 1.1.2)

component.selection: Tune the number of components

Description

Performs a multiple hypotheses testing procedure to choose the number of components in the splsda analysis

Usage

component.selection(object,alpha,showProgress=TRUE)

Arguments

object

a `bootsPLS' object, as obtained from bootsPLS

alpha

Level of the test

showProgress

Logical. If TRUE, shows the progress of the algorithm.

Value

A 'component.selection' object is returned for which plot is available.

pval

pvalue obtained from the testing procedure.

opt

Number of components chosen by the procedure

object

input `bootsPLS' object

alpha

input level of the test

Details

The testing procedure evaluates the gain in classification accuracy when a new PLS-component is added. This is done by on-sided t-test of level alpha applied on the classification accuracy obtained in the `bootsPLS' object. See the reference below for more details on the multiple testing procedure.

References

Rohart et al. (2016). A Molecular Classification of Human Mesenchymal Stromal Cells. PeerJ, DOI 10.7717/peerj.1845

See Also

plot.component.selection, fit.model, prediction

Examples

# NOT RUN {
data(MSC)
X=MSC$X
Y=MSC$Y
dim(X)
table(Y)

boot=bootsPLS(X=X,Y=Y,ncomp=3,many=5,kCV=5)

comp=component.selection(boot)
# }