R help - Nov 2004 - Performing regression using R & C

Dear All,
	Is it possible to perform OLS using C code? I am trying to
optimize a n-period "moving window" OLS on a huge dataset hence was
wondering if such a thing is possible.

	Ideally the solution that I am looking for would involve a
C-code accepting two float arrays and returning back computed parameters
such as t-stat, coefficient etc. 

	I have glanced thru the FAQ's and tried to google this
information but wasn't able to find anything truly relevant, hence would
really appreciate your help on this one.


Thanks.

Manoj

I have found "Numerical Recipes in C" to be extremely
helpful in my statistical studies.  OLS is described
in detail in this book.

Best,

    Greg


--- Manoj - Hachibushu Capital <Wanzare at HCJP.com>
wrote:
> Dear All,
> 	Is it possible to perform OLS using C code? I am
> trying to
> optimize a n-period "moving window" OLS on a huge
> dataset hence was
> wondering if such a thing is possible.
> 
> 	Ideally the solution that I am looking for would
> involve a
> C-code accepting two float arrays and returning back
> computed parameters
> such as t-stat, coefficient etc. 
> 
> 	I have glanced thru the FAQ's and tried to google
> this
> information but wasn't able to find anything truly
> relevant, hence would
> really appreciate your help on this one.
> 
> 
> Thanks.
> 
> Manoj
> 
> ______________________________________________
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> http://www.R-project.org/posting-guide.html
>

> 	Is it possible to perform OLS using C code? I am trying to
> optimize a n-period "moving window" OLS on a huge dataset hence
was
> wondering if such a thing is possible.
>
> 	Ideally the solution that I am looking for would involve a
> C-code accepting two float arrays and returning back computed 
> parameters
> such as t-stat, coefficient etc.
It is probably not worth trying to call R to do OLS from C.  I would 
look at GSL:

http://www.gnu.org/software/gsl/manual/gsl-ref_toc.html

GSL has a simple but elegant C interface for doing OLS and weighted 
least squares.  It will give you the covariance matrix of the model 
parameters, from which you can derive t-stats.

Jim M