R help - Sep 2003 - help for performing regressions based on combination of predictors

Dear All,

I would like to perform linear regressions based on Y
and all of the combinations of the five predictors,
i.e.,(y,x1,x2),(y,x1,x3),....,(y,x1,x2,x4,x5),....,(y,x1,x2,x3,x4,x5).

Is there any quick way to do it instead of repeat
performing regressions for 31 times? Or, is there 
any method to manipulate the dataset into the 31
combinations?

Thanks for your help!

Thanks! However, what I mean is performing 31
regressions based on the combinations of the
predictors. I don't consider interaction in 
this case. So, the regressions are like
lm(y~x1+x2) or lm(Y~x1+x2+x3),or lm(y~x1+x2+x4)
...etc.

--- Patrick Connolly <p.connolly at hortresearch.co.nz>
wrote:
> On Sun, 31-Aug-2003 at 06:06PM -0700, Lily wrote:
> 
> |> Dear All,
> |> 
> |> I would like to perform linear regressions based
> on Y
> |> and all of the combinations of the five
> predictors,
> |>
>
i.e.,(y,x1,x2),(y,x1,x3),....,(y,x1,x2,x4,x5),....,(y,x1,x2,x3,x4,x5).
> |> 
> |> Is there any quick way to do it instead of repeat
> |> performing regressions for 31 times? Or, is there
> 
> |> any method to manipulate the dataset into the 31
> |> combinations?
> 
> Probably, but it's simpler to put them all in the
> formula:
> 
> lm(y ~ x1 * x2 * x3 * x4 *x5)
> 
> 
> -- 
> Patrick Connolly
> HortResearch
> Mt Albert
> Auckland
> New Zealand 
> Ph: +64-9 815 4200 x 7188
>
~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~
> I have the world`s largest collection of seashells.
> I keep it on all
> the beaches of the world ... Perhaps you`ve seen it.
>  ---Steven Wright 
>
~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~

On 31 Aug 2003 at 18:06, Lily wrote:


Have you tried 
library(leaps)
library(help=leaps)
?

Kjetil Halvorsen
> Dear All,
> 
> I would like to perform linear regressions based on Y
> and all of the combinations of the five predictors,
> i.e.,(y,x1,x2),(y,x1,x3),....,(y,x1,x2,x4,x5),....,(y,x1,x2,x3,x4,x5).
> 
> Is there any quick way to do it instead of repeat
> performing regressions for 31 times? Or, is there 
> any method to manipulate the dataset into the 31
> combinations?
> 
> Thanks for your help!
> 
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