
Have a look at
car: Companion to Applied Regression package and different functions

Good luck

Federico



> From: chris@trickysolutions.com.au
> Date: Mon, 23 Apr 2012 10:11:19 +1000
> To: 13184@stud.leuphana.de
> CC: r-sig-ecology@r-project.org
> Subject: Re: [R-sig-eco] how-to identify redundant predictors
> 
> U should be able to get pretty close to what u want using the methods
> u've mentioned.
> 
> Seems to me your after an analysis that answers this question 'find me
> the 5 variables that explain the most amount of response variation,
> and also have the least correlation'
> 
> I believe standard model fitting methods using r-squared as the
> criteria answers the first half of that question, but it doesn't
> explicitly try to find uncorrelated predictors.
> 
> HOWEVER, if u fit predictors one at a time using the right SS then it
> may be implicitly doing this since the correlated part in subsequently
> added predictors should have already been fit? Im  thinking out loud
> here so contradictory comments are welcome.
> 
> The trick would be using the right fitting algorithm, I'm not sure if
> likelihood would work it might need to be something that fits each
> predictor one at a time.
> 
> If u do  find a 'black box' method I'd be interested to hear about it.
> 
> 
> 
> Chris Howden
> Founding Partner
> Tricky Solutions
> Tricky Solutions 4 Tricky Problems
> Evidence Based Strategic Development, IP Commercialisation and
> Innovation, Data Analysis, Modelling and Training
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> (mobile) 0410 689 945
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> 
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> On 21/04/2012, at 19:05, C Hess <13184@stud.leuphana.de> wrote:
> 
> > dear list,
> >
> > my actual task in the process of fitting an lme()-model is to identify and remove redundant predictors before using them as fixed effects.
> >
> > to get an overview and pick a group of final predictors i use the correlation-coefficients cor() and a pca prcomp()
> >
> > trying and testing seems an essential way in the process of model fitting, but maybe there is another way/method to get a list of predictors in a more structured way like: this are the top 5 predictors with the fewest correlation, or something else
> >
> > thanks
> > CH
> >
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