Employing a strategy of sampling of alternatives is necessary for various transportation models that have to deal with large choice-sets. In this article, we propose a method to obtain consistent, asymptotically normal and relatively efficient estimators for Logit Mixture models while sampling...

We propose a methodology to achieve consistency, asymptotic normality and efficiency, while sampling alternatives in Multivariate Extreme Value (MEV) models, extending a previous result for Logit. We illustrate the methodology and study the finite sample properties of the estimators using Monte...

In this study, we use a first-order spatial autoregressive formulation to model the correlation among the errors of a linear demand equation that explains origin-destination flows. The process splits the error term for each observation into a weighted sum of all the other errors and a purely...

The Multinomial Probit (MNP) formulation provides a very general framework to allow for inter-dependent alternatives in discrete choice analysis. Up until recently, its use was rather limited, mainly because of the computational difficulties associated with the evaluation of the choice...

In discrete choice analysis, the multinational probit (MNP) provides the most flexible framework to allow for general interdependencies among the alternatives. These interdependencies are usually modeled through the correlation structure of the error term. This framework suffers from two serious...