[R] stepwise variable selection with multiple dependent variables
Mitchell Maltenfort
mmalten at gmail.com
Fri Feb 10 23:56:50 CET 2012
"Anova.mlm" would be one way to do model selection.
On Fri, Feb 10, 2012 at 4:29 PM, Fugate, Michael L <fugate at lanl.gov> wrote:
> Good Day,
>
> I fit a multivariate linear regression model with 3 dependent variables and several predictors using the lm function. I would like to use stepwise variable selection to produce a set of candidate models. However, when I pass the fitted lm object to step() I get the following error:
>
> Error from R:
> Error in drop1.mlm(fit, scope$drop, scale = scale, trace = trace, k = k, :
> no 'drop1' method for "mlm" models
>
> My dependent data is in the matrix ymat where ymat is 35 rows by 3 columns. The predictors are in X where X is 35 by 6
>
> The steps I used were:
> m.fit <- lm(ymat ~ ., data=X)
> m.step <- step(m.fit)
>
> If variable selection is not possible with step() is there another package that will perform variable selection in a multivariate setting?
>
> System information:
> platform x86_64-apple-darwin9.8.0
> arch x86_64
> os darwin9.8.0
> system x86_64, darwin9.8.0
> status
> major 2
> minor 13.1
> year 2011
> month 07
> day 08
> svn rev 56322
> language R
> version.string R version 2.13.1 (2011-07-08)
>
> Thanks in advance.
>
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