Search Results
Search type | Search syntax |
---|---|
Tags | [tag] |
Exact | "words here" |
Author |
user:1234 user:me (yours) |
Score |
score:3 (3+) score:0 (none) |
Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
Views | views:250 |
Code | code:"if (foo != bar)" |
Sections |
title:apples body:"apples oranges" |
URL | url:"*.example.com" |
Saves | in:saves |
Status |
closed:yes duplicate:no migrated:no wiki:no |
Types |
is:question is:answer |
Exclude |
-[tag] -apples |
For more details on advanced search visit our help page |
A multivariate, discrete probability distribution used to describe the results of a random experiment where each of $n$ outcomes are placed into one of $k$ nominal categories.
4
votes
test multicollinearity for multinomial logit regression
Multicollinearity
The issue seems to be that colldiag() needs a model parameter, which is not appended to the model fit by default in multinom(). But if you set model = TRUE in the multinom call, the …
4
votes
1
answer
892
views
Using {rms} package for multinomial logit
Is it possible to use the rms package to model multinomials logits, or elsewise to model several binary logits to achieve the same effect? I am aware that there are many other packages specifically de …
1
vote
Accepted
Using {rms} package for multinomial logit
The answer is no. Having delved into this myself, it appears that it is not possible at the moment. However, it could be accomplished in the future were someone smarter than me to put some effort into …
3
votes
Confidence interval for predicted probabilities
You can accomplish this with the effects package. Now, for a reproducible example:
library(nnet)
set.seed(892)
x <- c(rnorm(100, 10, 1))
y <- factor(rep_len(1:3, 100))
fit <- multinom(y ~ x)
Th …