cov2corr: Convert Covariance into Correlation Matrix

Description Usage Arguments Value Examples

View source: R/cov2corr.R

Description

Given a covariance matrix, return a correlation matrix that has unit diagonals. We strictly impose (and check) whether the given input is a symmetric matrix of full-rank.

Usage

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cov2corr(mat)

Arguments

mat

a (p\times p) covariance matrix.

Value

a (p\times p) correlation matrix.

Examples

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# generate an empirical covariance scaled
prep_mat = stats::cov(matrix(rnorm(100*10),ncol=10))
prep_vec = diag(as.vector(stats::runif(10, max=5)))
prep_cov = prep_vec%*%prep_mat%*%prep_vec

# compute correlation matrix
prep_cor = cov2corr(prep_cov)

# visualize
opar <- par(no.readonly=TRUE)
par(mfrow=c(1,2), pty="s")
image(prep_cov, axes=FALSE, main="covariance")
image(prep_cor, axes=FALSE, main="correlation")
par(opar)

maotai documentation built on Feb. 3, 2022, 5:09 p.m.