Hi,
While exploring how summary.lm generated its output I came across a
section that left me puzzled.
at around line 57
R <- chol2inv(Qr$qr[p1, p1, drop = FALSE])
se <- sqrt(diag(R) * resvar)
I'm hoping somebody could explain the logic of these to steps or
alternatively point me in the direction of a text that will explain
these steps.
In particular I'm puzzled what is the relationship between QR
factorization and the cholesky factorization such that one can give a
(sort of ) R matrix as a parameter of chol2inv(). I say sort of R
matrix as the matrix generated by Qr$qr[p1, p1, drop = FALSE] has a
lower triangle with non zero entries although the upper triangle
corresponds to the values in the R matrix.