Journal
BIOMETRICS
Volume 56, Issue 3, Pages 742-747Publisher
INTERNATIONAL BIOMETRIC SOC
DOI: 10.1111/j.0006-341X.2000.00742.x
Keywords
Gaussian hidden Markov model; likelihood-ratio test; multivariate hidden Markov model; temporal graphical model
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We consider hidden Markov models as a versatile class of models for weakly dependent random phenomena. The topic of the present paper is likelihood-ratio testing for hidden Markov models, and we show that, under appropriate conditions, the standard asymptotic theory of likelihood-ratio tests is valid. Such tests are crucial in the specification of multivariate Gaussian hidden Markov models, which we use to illustrate the applicability of our general results. Finally, the methodology is illustrated by means of a real data set.
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