On the Viterbi process with continuous state space
classification
🧮 math.ST
math.PRstat.TH
keywords
continuoushiddenpathprocessspacestateconsideredconvergence
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This paper deals with convergence of the maximum a posterior probability path estimator in hidden Markov models. We show that when the state space of the hidden process is continuous, the optimal path may stabilize in a way which is essentially different from the previously considered finite-state setting.
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