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 > > ______________________________________________ > [email protected] 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, [EMAIL PROTECTED] 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 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
