sPLSDACV: CV function for a sPLSDA model

In singha53/amritr: Accessory Functions Used by Amrit Singh

Description

takes in predited weights and true labels and determines performance characterisitcs

Usage

sPLSDACV(X, Y, keepX, ncomp, M, folds, progressBar, filter, topranked)

Arguments

X	nxp dataset
Y	vector of phenotype labels with names(Y) == rownames(X)
keepX	(# of variables to select per component)
ncomp	number of components
M	Number of folds in the cross-validation
folds	list of elements (sample indices) for the M folds
progressBar	display progress bar or not (TRUE/FALSE)
filter	apply no filter "none" or a p.value filter "p.value
topranked	select the top significant variables based on limma

singha53/amritr documentation built on July 21, 2019, 3:46 p.m.