From: <Bill.Venables_at_csiro.au>

Date: Wed 13 Apr 2005 - 09:57:56 EST

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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 Received on Wed Apr 13 10:05:41 2005

Date: Wed 13 Apr 2005 - 09:57:56 EST

Alexandre,

I have a couple of remarks to make, not all of which you might find immediately helpful, I regret to say.

- The choice between using predictors linearly or in factor versions is a modelling choice that is in no way specific to multinom. It is a general aspect of modelling that has to be faced in a whole variety of situations. Indeed the full spectrum of choices is much wider than this: linear, polynomials, splines, different sorts of splines, harmonic terms, factors, ... In fact the idea behind gam's was really to allow some of this extensive field of choices to be model driven, but I digress. Point 1: you need to learn about modelling first and then apply it to multinom.
- It is curious to me that someone could be interested in multinomial models per se. Usually people have a context where multinomial models might be one approach to describing the situation in a statistically useful way. Another could be something like classification trees. The context is really what decides what modelling choices of this kind might be sensible.
- There is an obvious suggestion for one reference, a certain notorious blue and yellow book for which multinom is part of the support software. I believe they discuss some of the alternatives as well, like classification trees, and some of the principles of modelling, but it's been a while since I read it...
- Frank Harrell recently issued an excellent article on this list on brain surgery in a hurry to which you may usefully refer. I believe it was on April 1.

Bill Venables.

-----Original Message-----

From: r-help-bounces@stat.math.ethz.ch

[mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Alexandre Brito
Sent: Wednesday, 13 April 2005 8:20 AM

To: r-help@stat.math.ethz.ch

Subject: [R] factors in multinom function (nnet)

Dear All:

I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not.

I had posted earlier this example (thanks for the reply ronggui):

worms <- data.frame(year = rep(2000:2004, c(3,3,3,3,3)),

age = rep(1:3, 5), mud = c(2,5,0,8,7,7,5,9,14,12,8,7,5,13,11), sand = c(4,7,13,4,14,13,20,17,15,23,20,9,35,27,18), rocks = c(2,6,7,9,3,2,2,10,5,19,13,17,11,20,29))

k <- as.matrix(worms[,3:5])

(mud, sand and rocks are factors; age and year are predictors)

Now there are several possibilities:

m1 <- multinom(k ~ year+age, data = worms) m2 <- multinom(k ~ factor(year)+age, data = worms) m3 <- multinom(k ~ year+factor(age), data = worms) m4 <- multinom(k ~ factor(year)+factor(age), data = worms) m5 <- multinom(k ~ year:age, data = worms) m6 <- multinom(k ~ year*age, data = worms) m7 <- multinom(k ~ factor(year):age, data=worms) m8 <- multinom(k ~ year:factor(age), data=worms)

and so on.

I am far from an expert on this, and I would like to learn more about the utilization of multinom function in R and the kind of doubts I described above. So I hope that someone can recommend me some references in this matter (internet, books...) if any is available.

Thanks in advance, best wishes

Alexandre

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide!

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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 Received on Wed Apr 13 10:05:41 2005

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