[R] weights in multinom
Prof Brian Ripley
ripley at stats.ox.ac.uk
Tue Jun 27 13:21:24 CEST 2006
See the references for ?multinom and ?nnet: this is covered in my 1996
book.
On Tue, 27 Jun 2006, Jol, Arne wrote:
> Best R Help,
>
> I like to estimate a Multinomial Logit Model with 10 Classes. The
> problem is that the number of observations differs a lot over the 10
> classes:
>
> Class | num. Observations
> A | 373
> B | 631
> C | 171
> D | 700
> E | 87
> F | 249
> G | 138
> H | 133
> I | 162
> J | 407
> Total: 3051
>
> Where my data looks like:
>
> x1 x2 x3 x4 Class
> 1 1,02 2 1 A
> 2 7,2 1 5 B
> 3 4,2 1 4 H
> 1 4,1 1 8 F
> 2 2,4 3 7 D
> 1 1,2 0 4 J
> 2 0,9 1 2 G
> 4 4 3 0 C
> . . . . .
>
> My model looks like:
> estmodel <- multinom(choice ~ x1 + x2 + x3 + x4, data = trainset)
>
> When I estimate the model and use the resulting model for prediction of
> 'new' observations the model has a bias towards the Classes with a large
> number of observations (A,B,D,J), the other classes are never predicted
> by the model.
>
> I thougth that the option "weights" of the multinom function could be
> usefull but I am not sure how to use this in the above case.
>
> Is there someone with experience regarding such a weigthing approach in
> multinom? If someone could help me with suggestions it would be great!
>
> Nice day,
> Arne
>
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--
Brian D. Ripley, ripley at 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
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