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Likelihood-Ratio Tests for Hidden Markov Models

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  • Paolo Giudici
  • Tobias Ryden
  • Pierre Vandekerkhove

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  • Paolo Giudici & Tobias Ryden & Pierre Vandekerkhove, 2000. "Likelihood-Ratio Tests for Hidden Markov Models," Biometrics, The International Biometric Society, vol. 56(3), pages 742-747, September.
    • Handle: RePEc:bla:biomet:v:56:y:2000:i:3:p:742-747
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2000.00742.x
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    References listed on IDEAS

    as
    1. Leroux, Brian G., 1992. "Maximum-likelihood estimation for hidden Markov models," Stochastic Processes and their Applications, Elsevier, vol. 40(1), pages 127-143, February.
    2. Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998. "Stylized facts of daily return series and the hidden Markov model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244.
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    Cited by:

    1. Dannemann, Jorn & Holzmann, Hajo, 2008. "The likelihood ratio test for hidden Markov models in two-sample problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1850-1859, January.
    2. Rachel MacKay Altman, 2004. "Assessing the Goodness-of-Fit of Hidden Markov Models," Biometrics, The International Biometric Society, vol. 60(2), pages 444-450, June.
    3. Roberto Colombi & Sabrina Giordano, 2011. "Testing lumpability for marginal discrete hidden Markov models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(3), pages 293-311, September.
    4. Bolano, Danilo & Berchtold, André, 2016. "General framework and model building in the class of Hidden Mixture Transition Distribution models," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 131-145.
    5. Jörn Dannemann & Hajo Holzmann, 2008. "Likelihood Ratio Testing for Hidden Markov Models Under Non‐standard Conditions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(2), pages 309-321, June.
    6. Tim Sainburg & Marvin Thielk & Timothy Q Gentner, 2020. "Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-48, October.
    7. Max Greenfeld & Dmitri S Pavlichin & Hideo Mabuchi & Daniel Herschlag, 2012. "Single Molecule Analysis Research Tool (SMART): An Integrated Approach for Analyzing Single Molecule Data," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-12, February.

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