[R] question about how summary.lm works

[Peter Dalgaard]

Dominic Barraclough <dominicb at cvs.rochester.edu> writes:

> 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.

It's fairly easy, at least if we ignore the pivoting. We want
inv(X'X) where X is the design matrix, and we have X=QR where Q has
orthogonal columns. So Q'Q is the identity and X'X = R'R, i.e. R is a
Choleski factor of X'X, and we can use chol2inv to get to the inverse
of X'X. The rest is storage issues.

-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907