ABSTRACT
Statistical approaches to study continuous data (ordinary least squares regression) and discrete data (logit and probit models) have been used for decades in the analysis of transportation data. However, researchers have also identified a class of transportation-related problems that involve interrelated discrete and continuous data. Examples include consumers’ choice of the type of vehicle to own (discrete) and the number of kilometers to drive it (continuous), choice of route (discrete) and driving speed (continuous), and choice of trip-generating activity (discrete) and duration in the activity (continuous).
