computeRVmat: Compute a similarity or dissimilarity matrix with all...

In jeffreydurieux/TwostepClustering3way: Two step clustering of three way data

Description

This function computes all pairwise modified RV-coefficients between the matrices that are stored in the DataList object

Usage

computeRVmat(DataList = DataList, dist = TRUE, verbose = TRUE)

Arguments

DataList	a list with N matrices
dist	boolean, if TRUE a distance matrix is returned, if FALSE a similarity matrix is returned
verbose	if TRUE a progress bar is printed to the console

Value

a NxN similarity matrix or a dist object (dependening on the dist argument)

See Also

modRV, icaList

Examples

Mat <- matrix(rnorm(1000), 100)
SVD <- svd(Mat)
X <- vector(mode = 'list', length = 10)
for(i in 1:5){
X[[i]] <- SVD$u[,-i] %*% diag(SVD$d[-i]) %*% t(SVD$v[,-i])
}
X[[6]] <- matrix(rnorm(1000, mean = 0), 100)
SVD <- svd(X[[6]])
for(i in 6:10){
X[[i]] <- SVD$u[,-(i-5)] %*% diag(SVD$d[-(i-5)]) %*% t(SVD$v[,-(i-5)])
}

RVmat <- computeRVmat(DataList = X, dist = FALSE, verbose = TRUE)
heatmap(RVmat)

jeffreydurieux/TwostepClustering3way documentation built on Oct. 13, 2020, 2:33 a.m.