Bayesian estimation of multinomial probit model for commuter mode choice

In this paper, we estimate a multinomial probit model of commuter mode choice using the Bayesian approach with Gibbs sampling. This method constructs a Markov chain Gibbs sampler that can be used to draw directly from the exact posterior distribution and perform finite sample likelihood inference. Our results show that computes function using this method is quite accurate; the algorithm can be much faster to converge than either the procedure of classical estimation method.