[R] stepwise variable selection with multiple dependent variables

[Fugate, Michael L]

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.