Discrete choice modeling is widely applied in transportation studies. However, the need to
consider correlation between observations creates a challenge. In spatial econometrics, a …

In discrete choice analysis, the multinational probit (MNP) provides the most flexible
framework to allow for general interdependencies among the alternatives. These …

This paper evaluates the ability of the maximum approximate composite marginal likelihood
(MACML) estimation approach to recover parameters from finite samples in mixed cross …

This paper investigates the factors that affect household automobile and motorcycle
ownership in large metropolitan areas. Extensive geocoded trip data from Athens, Greece …

This paper formulates a multidimensional choice model system that is capable of handling
multiple nominal variables, multiple count dependent variables, and multiple continuous …

Many transportation-related behaviors involve multinomial discrete response in a temporal
and spatial context. These include quality of paved roadway sections over time, evolution of …

The discrete choice modeling paradigm and in particular the logit model are research topics
that have been continuously developed and refined for years in the field of transportation …

This paper develops a blueprint (complete with matrix notation) to apply Bhat's (2011)
Maximum Approximate Composite Marginal Likelihood (MACML) inference approach for the …

Integrated models for multiple decision variables, not necessarily from the same family, are
becoming possible thanks to the advances in econometrics and in the estimation …

Much has been written on the techniques for dealing with spatial dependence, spatial lag
and spatial error, in continuous econometric models (eg, Anselin, 1980, 1990; Anselin and …