[R] Forward Stepwise regression based on partial F test

2005-02-24 Thread Smit, Robin
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
[EMAIL PROTECTED]
http://www.automotive.tno.nl/est http://www.automotive.tno.nl/est 



  
 

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Re: [R] Forward Stepwise regression based on partial F test

2005-02-24 Thread Frank E Harrell Jr
Smit, Robin wrote:
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
Robin,
If you are looking for a method that does not offer the best predictive 
accuracy and that violates every aspect of statistical inference, you 
are on the right track.  See 
http://www.stata.com/support/faqs/stat/stepwise.html for details.

--
Frank E Harrell Jr   Professor and Chair   School of Medicine
 Department of Biostatistics   Vanderbilt University
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Re: [R] Forward Stepwise regression based on partial F test

2005-02-24 Thread Alex
Robin,

You may see leaps() (package leaps). It deals with all subsets regression 
considering several chosen criteria.

beste Regards,
Alex



 models -- Início da mensagem original ---
De: [EMAIL PROTECTED]
Para: Smit, Robin [EMAIL PROTECTED]
Cc: r-help@stat.math.ethz.ch
Data: Thu, 24 Feb 2005 07:15:03 -0500
Assunto: Re: [R] Forward Stepwise regression based on partial F test
 Smit, Robin wrote:
  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

 Robin,

 If you are looking for a method that does not offer the best predictive
 accuracy and that violates every aspect of statistical inference, you
 are on the right track. See
 http://www.stata.com/support/faqs/stat/stepwise.html for details.

 --
 Frank E Harrell Jr Professor and Chair School of Medicine
 Department of Biostatistics Vanderbilt University

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