A double penalized maximum likelihood estimator is proposed for simultaneous order selection and parameter estimation in non-stationary hidden Markov models, outperforming AIC and BIC in simulation studies with misspecified models.
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Improved order selection method for hidden Markov models: a case study with movement data
A double penalized maximum likelihood estimator is proposed for simultaneous order selection and parameter estimation in non-stationary hidden Markov models, outperforming AIC and BIC in simulation studies with misspecified models.