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
--------------------------------------------
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@(protected)
http://www.automotive.tno.nl/est <http://www.automotive.tno.nl/est>
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