Title: Multinomial Logit Model

Supervisor: Thomas Yee

Prerequisites: STATS 310, STATS 330 and R programming skills

Abstract: The aim of this project is to improve the multinomial()
family function in the VGAM R package. The multinomial logit
model is the standard model for regressing a nominal categorical
response against a set of explanatory variables. It can suffer
from numerical problems with sparse data, however, bias reduction
can be a solution for this (Ding and Gentleman, JCGS, 2005). One
task is to implement this within the function. Also, we could write
functions to conduct a score test, as well as the Hausman-McFadden
test for independence of irrelevant alternatives (IIA). Time
permitting, another useful feature would be to handle the nested
multinomial logit model, however this would be quite a challenge.

This project would suit a student with good R programming skills
and has done STATS 310 and STATS 330.