Hidden Markov Models with Discrete Non-Parametric Observation Distributions

Fits hidden Markov models with discrete non-parametric observation distributions to data sets. The observations may be univariate or bivariate. 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. Auxiliary predictors are accommodated in the univariate setting.


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install.packages("hmm.discnp")

2.1-12 by Rolf Turner, 7 days ago


Browse source code at https://github.com/cran/hmm.discnp


Authors: Rolf Turner


Documentation:   PDF Manual  


GPL (>= 2) license


Imports nnet


See at CRAN