The function in package nnet for 'Multinomial Logit Regression' is called
multinom() and not nnet(). You seem not to have used it, and therein lies
your error.
If you need more help, multinom() is support software for a book (see
library(help=nnet)), and the book has extensive worked examples.
> Hi again. I believe that I described the things bad before.
>
> I want to make the analysis with a sample data (train.set) of dataset for
> later see if the predictions adjust to the rest of data non selected with
> the sample train.
>
> Then, of the same form in glm:
>
> library(nnet)
> net <-
Hi again. I believe that I described the things bad before.
I want to make the analysis with a sample data (train.set) of dataset for
later see if the predictions adjust to the rest of data non selected with
the sample train.
Then, of the same form in glm:
library(nnet)
net <- nnet(response.
Hi all,
I have a dataset with a response variable with three categories (1, 2, 3)
and a lot of continuous variables. I'd like to make a MLR with these
variables. I've been watching the libraries nnet and zelig for this purpose
but I don't understand them well.
I use a training sample data to ma
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