[R] weights in multinom
Jol, Arne
Arne.Jol at Unilever.com
Tue Jun 27 11:18:57 CEST 2006
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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