I have a design matrix of p regressors, n observations, and I am trying to compute the sample variance-covariance matrix of the parameters. I am trying to directly calculate it using svd.
I am using R, when I take svd of the design matrix, I get three components: a matrix $U$ which is $n \times p$, a matrix $D$ which is $1\times 3$ (presumably eigenvalues), and a matrix $V$ which is $3\times 3$. I diagonalized $D$, making it a $3\times 3$ matrix with 0's in the off-diagonals.
Supposedly, the formula for covariance is: $V D^2 V'$, however, the matrix does not match, nor is it even close to R's built in function,
Does anyone have any advice/references? I admit that I am a bit unskilled in this area.