sdpcor2cov: sdcor2cov

In ctsem: Continuous Time Structural Equation Modelling

sdcor2cov

Description

Converts a lower triangular matrix with standard deviations on the diagonal and partial correlations on lower triangle, to a covariance (or cholesky decomposed covariance)

Usage

sdpcor2cov(mat, coronly = FALSE, cholesky = FALSE)

Arguments

mat	input square matrix with std dev on diagonal and lower tri of partial correlations.
coronly	if TRUE, ignores everything except the lower triangle and outputs correlation.
cholesky	Logical. To return the cholesky decomposition instead of full covariance, set to TRUE.

Examples

testmat <- diag(exp(rnorm(5,-3,2)),5) #generate arbitrary std deviations
testmat[row(testmat) > col(testmat)] <- runif((5^2-5)/2, -1, 1) 
print(testmat)
covmat <- sdpcor2cov(testmat) #convert to covariance
cov2cor(covmat) #convert covariance to correlation

ctsem documentation built on Sept. 11, 2024, 9:06 p.m.