  This report introduces a parsimonious structure for mixture of autoregressive
models, where the weighting coefficients are determined through latent random
variables as functions of all past observations. These variables follow a
hidden Markov model. We modify EM and Baum-Welch algorithms to estimate the
parameters of the model.
