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Discrete mixtures of GEV models

By Stephane Hess, Michel Bierlaire and John W. Polak


Allowing for variations in behaviour across respondents is one of the most fundamental principles in discrete choice modelling, given that the assumption of a purely homogeneous population cannot in general (or ever) be seen to be valid. Two approaches have classically been used to address this problem; the use of deterministic segmentations of the population, and the use of a random continuous representation of variations in tastes across respondents. In this paper, we discuss an alternative approach, based on the use of discrete mixtures of underlying GEV models over a finite set of distinct support points. The paper presents two applications; one illustrating the performance of the model with the help of simulated data, and one showing, on real data, how the model can be used to test the validity of hypotheses such as the presence of individuals with zero valuations of travel-time changes

Topics: Mixed logit – discrete distributions – latent classes
Year: 2005
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