A penalized quasi-likelihood approach for estimating the number of states in a hidden markov model
In statistical applications of hidden Markov models (HMMs), one may have no knowledge of the number of hidden states (or order) of the model needed to be able to accurately represent the underlying process of the data. The problem of estimating the number of states of the HMM is thus a task of major...
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| Format: | Others |
| Language: | en |
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McGill University
2012
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| Online Access: | http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110634 |