How to organize a list of covariance pairs in a squared covariance matrix?

Question

I am working in R and I have a tibble composed of three columns:

• V1: the name of the first variable
• V2: the name of the second variable
• cov: the value of the covariance between V1 and V2.

This tibble is expanded over n columns for n covariance pairs.

I would like to get a matrix that looks like a classical covariance matrix, ie a square n x n matrix with the covariance pairs in it.

Any idea how could I implement this?

Answer 1

Something along the lines of

## find row/column names
n <- unique(c(dd$V1,dd$V2))
## construct matrix  
M <- matrix(NA, length(n),length(n), dimnames=list(n,n))
## fill in values
M[cbind(dd$V1,dd$V2)] <- dd$V3

If you only have the lower/upper triangle in your initial data set you'll need something like M[lower.tri(M)] <- t(M)[upper.tri(M)] to symmetrize ...