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.
|Date of publication||2016-04-08 11:33:08|
|Maintainer||Rolf Turner <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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