naive questions---
why is this not part of the standard R distribution? fast regression is
*not* an obscure need.
why would an se() function not be part of the standard R distribution, given
that coef() can be?
naive suggestion to add to the ?lm text
"The underlying low level functions, 'lm.fit' for plain, and
'lm.wfit' for weighted regression fitting." ADD: These can be
orders of magnitude faster.
thank you, everyone.
regards,
/iaw
----
Ivo Welch (ivo.we...@brown.edu, ivo.we...@gmail.com)
On Fri, Jan 8, 2010 at 9:08 AM, Dirk Eddelbuettel <e...@debian.org> wrote:
>
> On 8 January 2010 at 08:35, ivo welch wrote:
> | dear R experts---I am using the coef() function to pick off the
> coefficients
> | from an lm() object. alas, I also need the standard errors and I need
> them
> | fast. I know I can do a "summary()" on the object and pick them off this
> | way, but this computes other stuff I do not need. Or, I can compute (X'
> | X)^(-1) s^2 myself. Has someone written a fast se() function?
>
> Pages 72 and 73 of my most recent Intro to HPC tutorial [1] use Rcpp to
> access the GNU GSL to do just that: coefficients and covariance matrix of a
> standard y ~ X linear model.
>
> Pages 75 and 76 illustrate how the speed compares to both lm() and lm.fit()
> (hint: it is rather favourable).
>
> Page 74 tells you how to compile this if you use Rcpp (but you'd have to
> insert the slightly longer code from the tutorial document), this is now
> easier using the newest version of the inline package as detailed on my
> blog
> [2] but this has not yet been reflected in a new HPC tutorial.
>
> Hth, Dirk
>
>
> [1] http://dirk.eddelbuettel.com/papers/ismNov2009hpcTutorial.pdf
> [2] http://dirk.eddelbuettel.com/blog/2009/12/20#rcpp_inline_example
>
> --
> Three out of two people have difficulties with fractions.
>
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