R help - Aug 2007 - Sorting data for multiple regressions

So I am trying to perform a robust regression (fastmcd in the robust
package) on a dataset and I want to perform individual regressions based
on the groups within the data.  We have over 300 sites and we want to
perform a regression based on the day of week and the hour for every
site.  I was wondering if anyone knows of a "'by' command similar
to the
one used in SAS that automatically groups the data for the regressions.
If not, does anyone have any tips on how to split the data into smaller
sets and then perform the regression on each set.  I am new to R, so I
don't know all of the common work arounds and such.  At the moment the
only method I can think of is to split the data using condition
statements and manually running the regression on each set.  Thanks or
your help

-Paul
 
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Well, R has a by() function that does what you want, and its help page 
contains an example of doing regression by group.

(There are other ways.)

On Fri, 3 Aug 2007, Paul Young wrote:
> So I am trying to perform a robust regression (fastmcd in the robust
> package) on a dataset and I want to perform individual regressions based
fastmcd does not do regression ... or I would have adapted the ?by 
example to show you.
> on the groups within the data.  We have over 300 sites and we want to
> perform a regression based on the day of week and the hour for every
> site.  I was wondering if anyone knows of a "'by' command
similar to the
> one used in SAS that automatically groups the data for the regressions.
> If not, does anyone have any tips on how to split the data into smaller
> sets and then perform the regression on each set.  I am new to R, so I
> don't know all of the common work arounds and such.  At the moment the
> only method I can think of is to split the data using condition
> statements and manually running the regression on each set.  Thanks or
> your help
>
> -Paul

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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