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Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement

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  1. Tardy, Olivia & Lenglos, Christophe & Lai, Sandra & Berteaux, Dominique & Leighton, Patrick A., 2023. "Rabies transmission in the Arctic: An agent-based model reveals the effects of broad-scale movement strategies on contact risk between Arctic foxes," Ecological Modelling, Elsevier, vol. 476(C).
  2. Timo Adam & Roland Langrock & Christian H. Weiß, 2019. "Penalized estimation of flexible hidden Markov models for time series of counts," METRON, Springer;Sapienza Università di Roma, vol. 77(2), pages 87-104, August.
  3. Gianluca Mastrantonio, 2022. "The modelling of movement of multiple animals that share behavioural features," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(4), pages 932-950, August.
  4. Marius Ötting & Roland Langrock & Antonello Maruotti, 2023. "A copula-based multivariate hidden Markov model for modelling momentum in football," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 9-27, March.
  5. Andreas Koukorinis & Gareth W. Peters & Guido Germano, 2025. "Generative-Discriminative Machine Learning Models for High-Frequency Financial Regime Classification," Methodology and Computing in Applied Probability, Springer, vol. 27(2), pages 1-32, June.
  6. Floriane Cardiec & Sophie Bertrand & Matthew J Witt & Kristian Metcalfe & Brendan J Godley & Catherine McClellan & Raul Vilela & Richard J Parnell & François le Loc’h, 2020. "“Too Big To Ignore”: A feasibility analysis of detecting fishing events in Gabonese small-scale fisheries," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-19, June.
  7. Michela Gnaldi & Simone Del Sarto, 2024. "Validating Corruption Risk Measures: A Key Step to Monitoring SDG Progress," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 175(3), pages 1045-1071, December.
  8. Adam, Timo & Mayr, Andreas & Kneib, Thomas, 2022. "Gradient boosting in Markov-switching generalized additive models for location, scale, and shape," Econometrics and Statistics, Elsevier, vol. 22(C), pages 3-16.
  9. Marc A. Scott & Jean-Marie Goff & Jacques-Antoine Gauthier, 2024. "History matters: the statistical modelling of the life course," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 445-469, February.
  10. Antonello Maruotti & Antonio Punzo, 2021. "Initialization of Hidden Markov and Semi‐Markov Models: A Critical Evaluation of Several Strategies," International Statistical Review, International Statistical Institute, vol. 89(3), pages 447-480, December.
  11. Joseph D. Bailey & Edward A. Codling, 2021. "Emergence of the wrapped Cauchy distribution in mixed directional data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(2), pages 229-246, June.
  12. Lin, Yong & Huang, Mian, 2025. "Penalized composite likelihood estimation for hidden Markov models with unknown number of states," Statistics & Probability Letters, Elsevier, vol. 216(C).
  13. Kristina M Ceres & Ynte H Schukken & Yrjö T Gröhn, 2020. "Characterizing infectious disease progression through discrete states using hidden Markov models," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
  14. Anton Gerunov, 2023. "Stock Returns Under Different Market Regimes: An Application of Markov Switching Models to 24 European Indices," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 18-35.
  15. Marius Ötting & Dimitris Karlis, 2023. "Football tracking data: a copula-based hidden Markov model for classification of tactics in football," Annals of Operations Research, Springer, vol. 325(1), pages 167-183, June.
  16. Mevin B. Hooten & Ruth King & Roland Langrock, 2017. "Guest Editor’s Introduction to the Special Issue on “Animal Movement Modeling”," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(3), pages 224-231, September.
  17. Supratim Dutta & Ramesh Krishnamurthy, 2024. "Multiphasic movement and step-selection patterns of dispersed tigers in the central Indian landscape," PLOS ONE, Public Library of Science, vol. 19(10), pages 1-15, October.
  18. Valeriy Zakamulin, 2023. "Not all bull and bear markets are alike: insights from a five-state hidden semi-Markov model," Risk Management, Palgrave Macmillan, vol. 25(1), pages 1-25, March.
  19. Chimienti, Marianna & Desforges, Jean-Pierre & Beumer, Larissa T. & Nabe-Nielsen, Jacob & van Beest, Floris M. & Schmidt, Niels Martin, 2020. "Energetics as common currency for integrating high resolution activity patterns into dynamic energy budget-individual based models," Ecological Modelling, Elsevier, vol. 434(C).
  20. Roland Langrock & Timo Adam & Vianey Leos‐Barajas & Sina Mews & David L. Miller & Yannis P. Papastamatiou, 2018. "Spline‐based nonparametric inference in general state‐switching models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 179-200, August.
  21. Maruotti, Antonello & Petrella, Lea & Sposito, Luca, 2021. "Hidden semi-Markov-switching quantile regression for time series," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
  22. Ethan Lawler & Kim Whoriskey & William H. Aeberhard & Chris Field & Joanna Mills Flemming, 2019. "The Conditionally Autoregressive Hidden Markov Model (CarHMM): Inferring Behavioural States from Animal Tracking Data Exhibiting Conditional Autocorrelation," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(4), pages 651-668, December.
  23. De Gooijer, Jan G. & Henter, Gustav Eje & Yuan, Ao, 2022. "Kernel-based hidden Markov conditional densities," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
  24. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
  25. Giorgio E. Montanari & Marco Doretti, 2019. "Ranking Nursing Homes’ Performances Through a Latent Markov Model with Fixed and Random Effects," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 307-326, November.
  26. Giorgio Eduardo Montanari & Marco Doretti & Maria Francesca Marino, 2022. "Model-based two-way clustering of second-level units in ordinal multilevel latent Markov models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(2), pages 457-485, June.
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