Explores binary response interpretation, link functions, logistic regression, and model selection using deviances and information criteria.
Covers ARMA models for time series forecasting, discussing implications, properties of forecast error, challenges with predictions, and covariance models.
Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.
Introduces mixtures, covers discrete and continuous mixtures, explores examples, and discusses combining probit and logit models.
