En estimation bayésienne, lorsque le calcul explicite de la loi a posteriori du vecteur des paramètres à estimer est impossible, les méthodes de Monte-Carlo par chaînes de Markov (MCMC) [Robert and Casella, 1999] permettent théoriquement de fournir un échantillon approximativement...

This web appendix has three main purposes. First, we provide a more or less 'stand-alone' technical appendix that describes the estimation algorithm for the proposed attribute model using Markov Chain Monte Carlo techniques (sections A1 and A2). The reversible jump (RJ) algorithm (Green, 1995)...

Modeling consumer heterogeneity helps practitioners understand market structures and devise effective marketing strategies. In this research we study finite mixture specifications for modeling consumer heterogeneity where each regression coefficient has its own finite mixture, that is, an...