Logit
6
Estimation
Discrete Choice Model Estimation with R
Welcome
Introduction
1
Introduction
Logit
2
Drawing from Densities
3
Simulating from a Model
4
Maximum Likelihood Estimation
5
Optimization
6
Estimation
7
Code Performance
8
Bayesian Approach
Probit
9
Multinomial Probit
10
Nested Logit Model
11
GEV Logit
Mixed
12
Simulation-Assisted Estimation
13
Latent Class MNL Model
14
Mixed Logit Model
References
Appendices
A
Appendix
Logit
6
Estimation
6
Estimation
add
5
Optimization
7
Code Performance