Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.
Explores the nested logit model for discrete choice and its implications on choice behavior and parameter estimation.
Explores the application of Maximum Likelihood Estimation in binary choice models, covering probit and logit models, latent variable representation, and specification tests.
Introduces Discrete Choice Analysis, covering scale, depth, data collection, and statistical inference.
Covers the binary choice model, error term assumptions, specific constants, invariances, and distribution properties.
