
Achim:

 

Thanks a lot for your suggestions.

 

Tudor


 
> Date: Sun, 13 Jun 2010 00:26:08 +0200
> From: Achim.Zeileis@uibk.ac.at
> To: tudor_bodea@hotmail.com
> CC: r-help@r-project.org
> Subject: Re: [R] mob (party package) question
> 
> On Fri, 11 Jun 2010, tudor wrote:
> 
> >
> > Dear useRs:
> >
> > I try to use mob from the party package (thanks Achim and Co.!) to model
> > based recursive partition a data set. The model is a logistic regression
> > specified with model=glinearModel and family=binomial(). Running mob
> > results in a few warnings of the type: In glm.fit ... algorithm did not
> > converge. As I speculate that this may be due to an insufficient number of
> > iterations I am wondering if any of you knows how to pass arguments to
> > glm.fit from within mob (e.g., epsilon and maxit). All my attempts to do it
> > by myself failed. All suggestions are welcome.
> 
> Hmm, good point, currently the "control" argument to glm.fit() can not be 
> passed through mob() because this has an argument fo the same nam. I'll 
> add this to our list of improvements that need to be done.
> 
> You can try to work around this by writing your own StatModel driver, 
> e.g., glinearModel2. However, before doing that, I would try to see 
> whether this is really the problem. I guess it's more likely that there 
> are other problems with that particular subset, e.g., (quasi-)complete 
> separation or no variation in one of the variables. Simply set "verbose = 
> TRUE" when calling mob() and track which subset causes the error. Then you 
> can recreate that subset by simply calling subset() and checking whether 
> glm() or glm.fit() work appropriately on that sub-sample.
> 
> hth,
> Z
> 
> > My system: Windows XP, R2.10.1.
> >
> > Thank you.
> >
> > Tudor
> > -- 
> > View this message in context: http://r.789695.n4.nabble.com/mob-party-package-question-tp2252500p2252500.html
> > Sent from the R help mailing list archive at Nabble.com.
> >
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> > and provide commented, minimal, self-contained, reproducible code.
> >
 		 	   		  
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