On Thu, 2006-12-14 at 14:37 +, [EMAIL PROTECTED] wrote:
Dear all,
I am wondering why the step() procedure in R has the description 'Select a
formula-based model by AIC'.
I have been using Stata and SPSS and neither package made any reference to
AIC in its stepwise procedure, and I
You may want to look at a book that was published more recently than 17
years ago (computing has changed a lot since then). Doing stepwise
regression using p-values is one approach (and when p-values were the
easiest (only) thing to compute, it was reasonable to use them). But
think about how
Dear Jinsong Zhao,
In proc reg in SAS, selection=stepwise does (modified) forward selection. In
step() in R, the default method is backward when the scope argument is
absent. To do (modified) forward selection, you can specify an initial model
with only a constant, and use the scope argument to
Jinsong Zhao wrote:
Dear all,
I have encountered a problem when perform stepwise regression.
You have more problems than you know.
The dataset have more 9 independent variables, but 7 observation.
Why collect any data? You can get great fits using random numbers using
this procedure.
On Fri, 28 Apr 2006, Jinsong Zhao wrote:
Dear all,
I have encountered a problem when perform stepwise regression.
The dataset have more 9 independent variables, but 7 observation.
The functions in the leaps package can do subset selection for data sets
with more variables than
在 06-4-28，Jinsong Zhao[EMAIL PROTECTED] 写道：
Dear all,
I have encountered a problem when perform stepwise regression.
The dataset have more 9 independent variables, but 7 observation.
~I think
this is the problem.
In R, before
Liaw, Andy [EMAIL PROTECTED] writes:
one needs to be lucky to have the first few PCs correlate well to
the response in case of PCR.
Which is one reason PLSR is often preferred over PCR in at least the
field of chemometrics. Since the components of PLSR maximise the
covariance with the
On Tue, 03 Feb 2004 09:25:18 +0100
[EMAIL PROTECTED] (Bjørn-Helge Mevik) wrote:
Liaw, Andy [EMAIL PROTECTED] writes:
one needs to be lucky to have the first few PCs correlate well to
the response in case of PCR.
Which is one reason PLSR is often preferred over PCR in at least the
field
Frank Harrell wrote
I think you missed the point. None of the variable
selection procedures
will provide results that have a fair probability of
replicating in
another sample.
FH
And Jinsong Zhao answered
Do you mean different procedures will provide
different results? Maybe I don't
On Sun, 1 Feb 2004 20:03:36 -0800 (PST)
Jinsong Zhao [EMAIL PROTECTED] wrote:
--- Frank E Harrell Jr [EMAIL PROTECTED] wrote:
For the case of stepwise regression, I have found
that
the subsets I got using regsubsets() are
collinear.
However, the variables in SPSS's result are
On Sun, 1 Feb 2004, [gb2312] Jinsong Zhao wrote:
In the case of stepwise, SPSS gave out a model with 4 independent
variable, but with step(), R gave out a model with 10 and much higher
R2. Furthermore, regsubsets() also indicate the 10 variable is one of
the best regression subset. How to
On Sun, 1 Feb 2004 11:09:28 -0800 (PST)
Jinsong Zhao [EMAIL PROTECTED] wrote:
Dear all,
I am a newcomer to R. I intend to using R to do
stepwise regression and PLS with a data set (a 55x20
matrix, with one dependent and 19 independent
variable). Based on the same data set, I have done the
--- Frank E Harrell Jr [EMAIL PROTECTED] wrote:
On Sun, 1 Feb 2004 11:09:28 -0800 (PST)
Jinsong Zhao [EMAIL PROTECTED] wrote:
Dear all,
I am a newcomer to R. I intend to using R to do
stepwise regression and PLS with a data set (a
55x20
matrix, with one dependent and 19
--- Frank E Harrell Jr [EMAIL PROTECTED] wrote:
For the case of stepwise regression, I have found
that
the subsets I got using regsubsets() are
collinear.
However, the variables in SPSS's result are not
collinear. I wonder what I should do to get a same
or
better linear model.
Jinsong Zhao wrote:
Do you mean different procedures will provide different results? Maybe
I don't understand your email correctly. Now, I just hope I could get
a reasonable linear model using stepwise method in R, but I don't know
how to deal with collinear problem.
What Dr. Harrell means (in
Hello!
On Fri, 2003-07-18 at 10:44, wouter buytaert wrote:
Hello,
is there a function in R to do stepwise regression analysis (e.g. for
backward elimination)?
Try ?step and look at the options there.
Cheers,
Winfried
thanks,
Wouter
__
Or stepAIC in the MASS library. If you are adventurouos, you can
experiment with the poorly debugged stepAIC.c downloadable from
www.prodsyse.com.
spencer graves
Winfried Theis wrote:
Hello!
On Fri, 2003-07-18 at 10:44, wouter buytaert wrote:
Hello,
is there a function in R to do stepwise
Try,
help.search(stepwise)
It brings up the functions step() and stepAIC() from MASS.
Andrew Taylor wrote:
Hi,
S-PLUS includes the function stepwise which can use a variety of
methods to conduct stepwise multiple linear regression on a set of
predictors. Does a similar function exist in R?
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