MOOC
The logit model is the workhorse of choice modelers. But it has some limitations. In particular, some assumptions used to derive it may not be consistent with the behavioral reality. It may lead to erroneous forecast. We illustrated using the so-called "red bud-blue bus" paradox, and Multivariate Extre Value models, addressing some of these issues, are introduced.
The sampling procedure used to collect choice data has a critical impact on the model estimation procedure. We introduce classical sampling procedures, and analyze in details the implications for model estimation.
In our quest to address the limitations of the logit model, we introduce a new family of models, based on "mixtures". We define what mixtures are, how they can be calculated. We investigate several important modeling assumptions that they can cover.
Random utility relies on the rationality assumption for the decision-makers. We show that human beings are not always consistent with this assumption, and may exhibit