AIC model selection
True. But from the "Note" section of help(step) :
This is a minimal implementation. Use 'stepAIC' in package 'MASS'
for a wider range of object classes.
And from author(s) section :
B. D. Ripley: 'step' is a slightly simplified version of 'stepAIC'
in package 'MASS' (Venables & Ripley, 2002 and earlier editions).
I am not sure why the simplification was necessary but I would prefer
the slightly more comprehensive version. Besides I like the word AIC
reflected in the function of the name as it is using AIC criterion to do
stepwise selection.
Regards, Adai
On Mon, 2005-08-08 at 17:16 -0700, Kerry Bush wrote:
The last time I used it, the function step() was using AIC as model selection criteria as the default. It is in the base package so you don't have to refer to other fancy functions. --- Adaikalavan Ramasamy <ramasamy at cancer.org.uk> wrote:
Are you looking for possibly stepAIC from the package MASS ? Regards, Adai On Mon, 2005-08-08 at 16:39 -0600, Martin Kardos wrote:
Hello All; I need to run a multiple regression analysis and
use Akaike's Information
Criterion for model selection. I understand that
this command will give the
AIC value for specified models: AIC(object, ..., k = 2) with "..." meaning any other optional models for
which I would like AIC
values. But, how can I specify (in the place of
"...") that I want R to
perform an model selection prodecure based on
Akaike's Information Criterion
on a set of potential independent variables in a
model such as:
model.lm=lm(A~B+C+D+E+F+G) ? Thanks a million; Marty
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