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hmm.discnp (version 0.2-2)

Hidden Markov models with discrete non-parametric observation distributions.

Description

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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Version

Install

install.packages('hmm.discnp')

Monthly Downloads

234

Version

0.2-2

License

GPL (>= 2)

Maintainer

Rolf Turner

Last Published

May 19th, 2014

Functions in hmm.discnp (0.2-2)

lesionCount

Multiple sclerosis lesion counts for three patients.
sim.hmm

Simulate discrete data from a hidden Markov model.
pr

Probability of state sequences.
hmm

Fit a hidden Markov model to discrete data.
viterbi

Most probable state sequence.
fitted.hmm.discnp

Fitted values of a discrete non-parametric hidden Markov model.
colifCount

Coliform counts in sea-water samples
hmm.discnp-internal

Internal hmm.discnp functions.
sp

Calculate the conditional state probabilities.
logLikHmm

Log likelihood of a hidden Markov model
mps

Most probable states.