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MODEL SELECTION FOR MULTIVARIATE STOCHASTIC PROCESSES

We address the problem of model selection for a multivariate source with finite alphabet. Families of Markov models and model selection algorithms are generalized for the multivariate case. For Markovian sources our model selection procedures are consistent in the sense that, eventually, as the collected data grows, the sources Markov model will be retrieved exactly and it will be described with a minimal number of parameters.