From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>

Date: Tue 17 May 2005 - 15:42:29 EST

Date: Tue 17 May 2005 - 15:42:29 EST

On Mon, 16 May 2005, Brooks Miner wrote:

> Professor Ripley,

*>
**> Thanks very much. You comments were very helpful. I've got it (almost) all
**> figured out now. My model is for discrete data (discrete response AND
**> predictors). The issue I'm stuck on is that my saturated model does NOT
**> predict exactly; the constant is ~1874.052.
**>
**> Here is an example of my model with much less data, showing how the saturated
**> model does not predict exactly (constant ~ 440.6375).
*

Because you have an aggregated model: counts, not individual observations.

*>
**>
*

> library(nnet)

*> fem.labs<-
**> factor(c("Fem1","Fem2","Fem3","Fem4","Fem5","Fem6"),levels=c("Fem1","Fem
**> 2","Fem3","Fem4","Fem5","Fem6"))
**> site.labs<-factor(c("Site01","Site02","Site03","Site04"))
**> dyad.labs<-factor(c("M","H","U"),levels=c("M","H","U"))
**> data.table<-expand.grid(Site=site.labs, Female=fem.labs,Dyad=dyad.labs)
**> data<-
**> c(20,16,21,16,13,11,15,13,27,27,30,19,24,25,29,23,24,20,25,25,24,18,26,2
**> 0,2,0,2,2,1,1,0,1,3,3,3,6,4,3,2,4,2,1,3,1,3,4,1,1,5,11,4,9,1,3,0,1,3,3,0
**> ,8,4,4,1,5,6,11,4,6,3,8,3,9)
**> data.table<-structure(.Data=data.table[rep(1:
**> nrow(data.table),data),],row.names=1:length(data))
**> fit.saturated.model<-multinom(Dyad~Female*Site,data=data.table)
**> fit.saturated.model$deviance # Why is this NONZERO?
**>
**>
**> Am I setting up the regression for the saturated model incorrectly??
**>
**> Thanks in advance. . .
**>
**> - Brooks
**>
**> ----------------------------
**> Brooks Miner
**> Research Scientist
**> Laird Lab
**> UW Biology
**> 206.616.9385
**> http://protist.biology.washington.edu/Lairdlab/
**>
**> On May 13, 2005, at 10:41 PM, Prof Brian Ripley wrote:
**>
**>> By definition, the deviance is minus twice the maximized log-likelihood
**>> plus a const. In any of these models for discrete data, the saturated
**>> model predicts exactly, so the const is zero.
**>>
**>> There are worked examples in MASS4, the book multinom() supports.
**>>
**>> On Fri, 13 May 2005, Brooks Miner wrote:
**>>
**>>> Hi all,
**>>>
**>>> I'm working on a multinomial (or "polytomous") logistic regression using R
**>>> and have made great progress using multinom() from the nnet library. My
**>>> response variable has three categories, and there are two different
**>>> possible predictors. I'd like to use the likelihoods of certain models
**>>> (ie, saturated, fitteds, and null) to calculate Nagelkerke R-squared
**>>> values for various fitted models.
**>>>
**>>> My question today is simple: once I have fitted a model using multinom(),
**>>> how do I find the likelihood (or log likelihood) of my fitted model? I
**>>> understand that this value must be part of the $deviance or $AIC
**>>> components of the fitted model, but my understanding is too limited at
**>>> this point for me to know how to calculate the likelihood of my fitted
**>>> model from either of these outputs.
**>>>
**>>> Thanks in advance to any assistance offered. I'd be happy to provide an
**>>> example of my data and multinom() entries if that would help.
**>>>
**>>> Gratefully,
**>>>
**>>> - Brooks
**>>> ----------------------------
**>>> Brooks Miner
**>>> Research Scientist
**>>> Laird Lab
**>>> UW Biology
**>>> 206.616.9385
**>>> http://protist.biology.washington.edu/Lairdlab/
**>>>
**>>> ______________________________________________
**>>> R-help@stat.math.ethz.ch mailing list
**>>> https://stat.ethz.ch/mailman/listinfo/r-help
**>>> PLEASE do read the posting guide!
**>>> http://www.R-project.org/posting-guide.html
**>>>
**>>
**>> --
**>> Brian D. Ripley, ripley@stats.ox.ac.uk
**>> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
**>> University of Oxford, Tel: +44 1865 272861 (self)
**>> 1 South Parks Road, +44 1865 272866 (PA)
**>> Oxford OX1 3TG, UK Fax: +44 1865 272595
**>
**>
*

-- Brian D. Ripley, ripley@stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.htmlReceived on Tue May 17 16:53:24 2005

*
This archive was generated by hypermail 2.1.8
: Fri 03 Mar 2006 - 03:31:46 EST
*