I am hoping to get some advise on the following:
 
I am looking for an automatic variable selection procedure to reduce the
number of potential predictor variables (~ 50) in a multiple regression
model.
 
I would be interested to use the forward stepwise regression using the
partial F test. 
I have looked into possible R-functions but could not find this
particular approach. 
 
There is a function (stepAIC) that uses the Akaike criterion or Mallow's
Cp criterion. 
In addition, the drop1 and add1 functions came closest to what I want
but with them I cannot perform the required procedure. 
Do you have any ideas? 
 
Kind regards,
Robin Smit
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Business Unit TNO Automotive
Environmental Studies & Testing
PO Box 6033, 2600 JA Delft
THE NETHERLANDS

ph. +31 (0)15 269 7464
fax +31 (0)15 269 6874
robin.smit@tno.nl
http://www.automotive.tno.nl/est <http://www.automotive.tno.nl/est> 
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