[R] OLS variables

[John Fox]

Dear Leaf,

I assume that you're using lm() to fit the model, and that you don't really
want *all* of the interactions among 20 predictors: You'd need quite a lot
of data to fit a model with 2^20 terms in it, and might have trouble
interpreting the results. 

If you know which interactions you're looking for, then why not specify them
directly, as in lm(y ~  x1*x2 + x3*x4*x5 + etc.)? On the other hand, it you
want to include all interactions, say, up to three-way, and you've put the
variables in a data frame, then lm(y ~ .^3, data=DataFrame) will do it.
There are many terms in this model, however, if not quite 2^20.

The introductory manual that comes with R has information on model formulas
in Section 11.

I hope this helps,
 John 

--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox 
-------------------------------- 

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Leaf Sun
> Sent: Sunday, November 06, 2005 3:11 AM
> To: r-help at stat.math.ethz.ch
> Subject: [R] OLS variables
> 
> Dear all,
> 
> Is there any simple way in R that can I put the all the 
> interactions of the variables in the OLS model?
> 
> e.g.
> 
> I have a bunch of variables, x1,x2,.... x20... I expect then 
> to have interaction (e.g. x1*x2, x3*x4*x5... ) with some 
> combinations(2 way or higher dimensions). 
> 
> Is there any way that I can write the model simpler?
> 
> Thanks!
> 
> Leaf
> 
>