Generate covariance matrix from correlation matrix

Question

I have a correlation matrix:

a <- matrix(c(1, .8, .8, .8, 1, .8, .8, .8, 1), 3)

##      [,1] [,2] [,3]
## [1,]  1.0  0.8  0.8
## [2,]  0.8  1.0  0.8
## [3,]          


        

Answer 1

Building on S4M's answer, in base R, I would write this function:

cor2cov <- function(V, sd) {
  V * tcrossprod(sd)
}

tcrossprod will calculate the product of each combination of elements of the sd vector (equivalent to x %*% t(x)), which we then (scalar) multiply by the variance-covariance matrix

Here's a quick check that the function is correct using the built in mtcars data set:

all.equal(
  cor2cov(cor(mtcars), sapply(mtcars, sd)), 
  cov(mtcars)
)