hmm.discnp: Hidden Markov models with discrete non-parametric observation distributions. Fits hidden Markov models with discrete non-parametric observation distributions to data sets. Simulates data from such models. Finds most probable underlying hidden states, the most probable sequences of such states, and the log likelihood of a collection of observations given the parameters of the model.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Jouni Helske, Satu Helske: Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R (2017) arXiv
- Visser, Ingmar; Speekenbrink, Maarten: Comments on: “Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates” (2014)