Vegan (on CRAN) may be of help. Particularly look at the ordistep,
ordiR2step etc.
On Sun 13 Nov 2011 01:25:46 AM CST, David_Hewitt wrote:
On Sat, 12 Nov 2011, Michel Rapinski<[email protected]> wrote:
Hello,
There is a function in R's basic library (stats), step(), which allows
step by step selection of variables (forward, backward, both) on multiple
linear regression models based on AIC scores.
Unfortunately, and correct me if I am wrong, it only works for lm,
aov and
glm models.
The package AICcmodavg handles many other types of linear models. It's
on CRAN.
In the case of selecting variables for canonical analysis,
more specifically redundancy analysis (RDA), are there functions that
enables these same test on rda models? I figured that since RDA is
basically a multivariate extension of the multiple linear regression, it
should work, but no luck!
There are important differences between ordination and linear models.
Beyond
that, the issue of selecting important variables is far more complex than
just an automated routine to search through them for "significance"
(of any
kind). Patrick's recommendation to have a look at the book by Burnham and
Anderson is a good one -- start with pp 84-85 and section 4.4 (pp 167 ->).
I have succesfully managed to use the forward.sel() function in
library(packfor), for selecting variables in my multivariate RDA models,
but I also wish to do backward and alternating selection to help in the
selection of my variables.
Help will be greatly appreciated.
Michel
Michel Rapinski, MSc. Student
Inst. of Plant Biology Research, Montreal Botanical Garden
Université de Montréal
Montréal, QC H1X 2B2
Tel: 514.772-1710
Fax: 514.872.9406
[email protected]
University of Ottawa
[email protected]
Hi Minda,
AIC scores depend upon the statistical models used. I think R does the
best job of providing these scores, for example in the context of
multiple
linear regression and generalized linear models.
The literature on R or on stats using R is growing rapidly. You will
find
readable treatments of AIC in Crawley's 2007 R book or in Zuur et
al'sv2009 Mixed Effects Models and extensions in Ecology with R.
And do not forget to examine ( I am not sure read is a realistic option)
the valuable book by Burnham and Anderson 2002, Models Selection and
Multimodel Inference.
Patrick Foley
bees, fleas, flowers, disease
[email protected]
________________________________________
From: Minda Berbeco [[email protected]]
Sent: Wednesday, October 26, 2011 8:32 AM
To: [email protected]
Subject: [ECOLOG-L] AIC scores
Hello,
I am looking for recommendations for programs to use for calculating AIC
scores. I've looked into the AICcmodavg package with R, but the
associated
instructional material is not clear and I have not been able to get
it to
work. I hear that SAS is good as well, but have not found a good book
that
tells me how to create AIC scores (recommendations would be
appreciated).
I've also looked into SPSS, which according to IBM can create AIC
scores,
but have had no success.
Any recommendations for programs and clear associated instructional
material
with information on how to run the program, write the code etc. would be
greatly appreciated.
Thanks,
Minda Berbeco
Viticulture and Enology, UC Davis
[email protected]
