R package HiddenMarkov: Hidden Markov Models. Contains functions for the analysis of Discrete Time Hidden Markov Models, Markov Modulated GLMs and the Markov Modulated Poisson Process. It includes functions for simulation, parameter estimation, and the Viterbi algorithm. See the topic ”HiddenMarkov” for an introduction to the package, and ”Changes” for a list of recent changes. The algorithms are based of those of Walter Zucchini.

References in zbMATH (referenced in 11 articles )

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  1. Bulla, Jan (ed.); Langrock, Roland (ed.); Maruotti, Antonello (ed.): Guest editor’s introduction to the special issue on “Hidden Markov models: theory and applications” (2019)
  2. Francesco Bartolucci; Silvia Pandolfi; Fulvia Pennoni: LMest: An R Package for Latent Markov Models for Longitudinal Categorical Data (2017) not zbMATH
  3. Volodymyr Melnykov: ClickClust: An R Package for Model-Based Clustering of Categorical Sequences (2016) not zbMATH
  4. Wetzels, Ruud; Tutschkow, Darja; Dolan, Conor; van der Sluis, Sophie; Dutilh, Gilles; Wagenmakers, Eric-Jan: A Bayesian test for the hot hand phenomenon (2016)
  5. Zucchini, Walter; MacDonald, Iain L.; Langrock, Roland: Hidden Markov models for time series. An introduction using R (2016)
  6. Visser, Ingmar; Speekenbrink, Maarten: Comments on: “Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates” (2014)
  7. Wang, Ting; Bebbington, Mark; Harte, David: Markov-modulated Hawkes process with stepwise decay (2012)
  8. Christopher Jackson: Multi-State Models for Panel Data: The msm Package for R (2011) not zbMATH
  9. Visser, Ingmar: Seven things to remember about hidden Markov models: A tutorial on Markovian models for time series (2011)
  10. Bulla, Jan; Bulla, Ingo; Nenadić, Oleg: hsmm - An R package for analyzing hidden semi-Markov models (2010)
  11. Zucchini, Walter; MacDonald, Iain L.: Hidden Markov models for time series. An introduction using R (2009)