Description Usage Arguments Value Examples
Given a covariance matrix, return a partial correlation matrix that has unit diagonals. We strictly impose (and check) whether the given input is a symmetric matrix of full-rank.
1 | cov2pcorr(mat)
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mat |
a (p\times p) covariance matrix. |
a (p\times p) partial correlation matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # 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 and partial correlation matrices
prep_cor = cov2corr(prep_cov)
prep_par = cov2pcorr(prep_cov)
# visualize
opar <- par(no.readonly=TRUE)
par(mfrow=c(1,3), pty="s")
image(prep_cov, axes=FALSE, main="covariance")
image(prep_cor, axes=FALSE, main="correlation")
image(prep_par, axes=FALSE, main="partial correlation")
par(opar)
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