metapca: metapca

In bbuchsbaum/neuropls: neuroca: multiblock component analysis for neuroimaging data

metapca

Description

metapca

Usage

metapca(fits, ncomp = 2, scale_inner = FALSE)

Arguments

scale_inner

standardize first level components X1 <- matrix(rnorm(20*10), 20, 10) X2 <- matrix(rnorm(20*20), 20, 20) X3 <- matrix(rnorm(20*30), 20, 30) pc1 <- pca(X1, ncomp=10, preproc=center()) pc2 <- pca(X2, ncomp=10, preproc=center()) pc3 <- pca(X3, ncomp=10, preproc=center()) Xg <- cbind(X1,X2,X3) fits <- list(pc1,pc2,pc3) pfit <- metapca(fits, ncomp=15, scale_inner=TRUE) ncol(scores(pfit)) == 10

bbuchsbaum/neuropls documentation built on April 17, 2022, 8:46 a.m.