hmm.discnp v0.2-0

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by Rolf Turner

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.

Functions in hmm.discnp

Name Description
pr Probability of state sequences.
logLikHmm Log likelihood of a hidden Markov model
hmm Fit a hidden Markov model to discrete data.
sp Calculate the conditional state probabilities.
mps Most probable states.
hmm.discnp-internal Internal hmm.discnp functions.
fitted.hmm.discnp Fitted values of a discrete non-parametric hidden Markov model.
viterbi Most probable state sequence.
sim.hmm Simulate discrete data from a hidden Markov model.
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Details

Date 2013-09-30
License GPL (>= 2)
URL http://www.math.unb.ca/~rolf/
Packaged 2013-09-30 21:51:42 UTC; rolf
NeedsCompilation yes
Repository CRAN
Date/Publication 2013-10-01 07:42:59

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