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In this paper, we introduce a variant of hidden Markov models in which the transition probabilities between the states, as well as the emission distributions, are not constant in time but vary in a periodic manner. This class of models, which we will call seasonal hidden Markov models (SHMMs), is particularly useful in practice, as many applications involve a seasonal behaviour. However, up to now,...