ejikeugba / gofcat Goto Github PK

Hello,

I am still conducting tests for the JOSS review (openjournals/joss-reviews#4382).
I was testing the use of a nnet fitted model. I just took the example from the help of the function, which is a binary response model but I think it should work ?

library(nnet)
library(MASS)
example(birthwt)
bwt.mu <- multinom(low ~ ., bwt)
erroR(bwt.mu)
Rsquared(bwt.mu)

I obtain the following error:

Error: more than one column of fitted values for a binary model is not allowed

Hi,
Thanks for this package, I have a question while conducting some tests for the review ( openjournals/joss-reviews#4382 ).

What does happen if you have a variable called 'grp' in the data ? I suspect some results depending on the variable, see the snippet bellow, adapted from the README.

dt <- data.frame(y = ordered(rbinom(n,2,0.5)), x1 = factor(rbinom(n,2,0.7)), x2 = runif(n))
dt$grp = dt$x1
sp <- serp(y ~ x1 +x2, slope="parallel", link = "logit", reverse= TRUE, data = dt)
sp_grp <- serp(y ~ grp +x2, slope="parallel", link = "logit", reverse= TRUE, data = dt)

#Same results
hosmerlem(sp,tables = TRUE)
hosmerlem(sp_grp,tables = TRUE)

#different results
lipsitz(sp)
lipsitz(sp_grp)