Estimation in autoregressive models with Markov regime
classification
🧮 math.ST
stat.TH
keywords
markovautoregressivemodelshiddenregimealgorithmchainconsistency
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In this paper we derive the consistency of the penalized likelihood method for the number state of the hidden Markov chain in autoregressive models with Markov regimen. Using a SAEM type algorithm to estimate the models parameters. We test the null hypothesis of hidden Markov Model against an autoregressive process with Markov regime.
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