This paper describes and implements three computationally attractive procedures for nonparametric estimation of mixing distributions in discrete choice models. The procedures are specic types of the well known EM (Expectation-Maximization) algorithm based on three dierent ways of approximating...

A number of authors have discussed the possible advantages of conditioning parameter distributions on observed choices when working with Mixed Multinomial Logit models. However, the number of applications is still relatively small, partly due to a limited implementation in available software. To...

Maximum simulated likelihood (MSL) procedure is generally adopted in discrete choice analysis to solve complex models without closed mathematical formulation. This procedure differs from the maximum likelihood simply because simulated probabilities are inserted into the Log-Likelihood (LL)...

This paper describes a study undertaken to estimate a departure-time and mode-choice model for Stockholm. The model is segmented according to trip purpose, and a mixed - or error component - logit model is estimated. Estimation draws on stated preference data collected from drivers travelling...