On Jan 22, 2013, at 3:59 PM, Dimitri Liakhovitski wrote:
> I already looked. This help file for "loglin
> (http://127.0.0.1:12583/library/stats/html/loglin.html) says:
> "The Iterative Proportional Fitting algorithm as presented in Haberman (1972)
> is used for fitting the model. At most iter iterations are performed,
> convergence is taken to occur when the maximum deviation between observed and
> fitted margins is less than eps." And the default eps is 0.1
>
> So, is it then the convergence criterion used by glm when
> family=binomial("logit")?
> I just need to know for sure.
I assumed that you would follow the link on help(glm) to `glm.control` where
the convergence criteria is described and can be altered. The link to that help
page is at the end of the line that reads:
"control
a list of parameters for controlling the fitting process. For glm.fit this is
passed to glm.control."
The default epsilon is NOT 0.1
--
David.
>
> Thanks for confirming!
> Dimitri
>
>
>
> On Tue, Jan 22, 2013 at 6:37 PM, David Winsemius <dwinsem...@comcast.net>
> wrote:
>
> On Jan 22, 2013, at 2:55 PM, Dimitri Liakhovitski wrote:
>
> > Dear R-ers,
> >
> > I am running logistics regression using package "glm": glm(myDV ~ .,
> > data=mydata, family=binomial("logit"))
> >
> > I have a general question: in "glm" (binary logit) - what convergence
> > criterion is being used?
>
> You should look at the help page for `glm` (and follow the obvious links.)
> >
> > --
>
> David Winsemius
> Alameda, CA, USA
>
>
>
>
> --
> Dimitri Liakhovitski
> gfk.com
David Winsemius
Alameda, CA, USA
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