Before revision: Variational Bayes (VB) methods have emerged as a fast and computationally-efficient alternative to maximum simulated likelihood (MSL) and Markov chain Monte Carlo (MCMC) methods for the estimation of discrete choice models.
After revision: Variational Bayes (VB) , a method originating from machine learning, enables fast and scalable estimation of complex probabilistic models.