ctsem (version 3.0.4)

sdpcor2cov: 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, cholesky = FALSE)

Arguments

mat

input square matrix with std dev on diagonal and lower tri of partial correlations.

cholesky

Logical. To return the cholesky decomposition instead of full covariance, set to TRUE.

Examples

# NOT RUN {
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
# }