[R] multinomial logistic regression with equality constraints?

[Roger Levy]

Hi again Jasjeet, Walter,

I have a further question about an error message I get when running 
multinomRob.  I am simulating a dataset where I look at the effect of 
making a previous categorical choice on the probability of making the 
same choice later on.  Given the following code:


n <- 20
choice <- c("A","B","C")
intercepts <- c(0.5,0.3,0.2)
prime.strength <- rep(0.4,length(intercepts))
counts <- c()
for(i in 1:length(choice)) {
   u <- intercepts[1:length(choice)]
   u[i] <- u[i] + prime.strength[i]
   counts <- c(counts,rmultinomial(n = n, pr = multinomLogis(u)))
}
dim(counts) <- c(length(choice),length(choice))
counts <- t(counts)
row.names(counts) <- choice
colnames(counts) <- choice
data <- data.frame(Prev.Choice=choice,counts)

for(i in 1:length(choice)) {
   data[[paste("last",choice[i],sep=".")]] <- 
ifelse(data$Prev.Choice==choice[i],1,0)
}

multinomRob(list(A ~ last.A ,
                  B ~ last.B ,
                  C ~ last.C - 1 ,
                  ),
             data=data,
             print.level=1)


I get the following error:


multinomRob(): Grouped MNL Estimation
Error in if (logliklambda < loglik) bvec <- blambda :
	missing value where TRUE/FALSE needed
In addition: Warning message:
NaNs produced in: sqrt(sigma2GN)


It's not clear to me what this error means, or why the resulting dataset 
would be problematic for MLE estimation.

Many thanks once again!

Roger