[R] predict() works with the design matrix but throws error with some rows of that matrix

[Damir Cosic]

Hello,

I am having problems with predict() after a multinomial logit regression by
multinom(). I generate a design matrix with model.matrix() and use it to
estimate the model. Then, if I pass the entire design matrix to predict(),
it returns the same output as fitted(), which is expected. But if I pass
only a few rows of the design matrix, it throws this error:

Error in model.frame.default(Terms, newdata, na.action = na.omit, xlev
= object$xlevels) :    variable lengths differ (found for 'z') In addition:

Warning message: 'newdata' had 6 rows but variables found have 15 rows

This is a minimal example:

require(nnet)

y<-factor(rep(c(1,2,3),5), levels=1:3, labels=c("good","bad","ugly"))
x<-rnorm(15)+.2*rep(1:3,5)
z<-factor(rep(c(1,2,2),5), levels=1:2, labels=c("short","tall"))

df<-data.frame(y=y, x=x, z=z)
mm<-model.matrix(~x+z, data=df)[,2:3]
m<-multinom(y ~ x+z, data=df)

p1<-predict(m,mm,"probs")

p2<-predict(m,head(mm),"probs")

My actual goal is out-of-sample prediction, but I could not make it work
and, while debugging it, I reduced it to this problem.

Best,

Damir

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