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hmm.discnp (version 0.2-4)

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

205

Version

0.2-4

License

GPL (>= 2)

Maintainer

Rolf Turner

Last Published

April 8th, 2016

Functions in hmm.discnp (0.2-4)

colifCount

Coliform counts in sea-water samples
pr

Probability of state sequences.
sim.hmm

Simulate discrete data from a hidden Markov model.
viterbi

Most probable state sequence.
mps

Most probable states.
fitted.hmm.discnp

Fitted values of a discrete non-parametric hidden Markov model.
hmm.discnp-internal

Internal hmm.discnp functions.
logLikHmm

Log likelihood of a hidden Markov model
sp

Calculate the conditional state probabilities.
hmm

Fit a hidden Markov model to discrete data.
lesionCount

Multiple sclerosis lesion counts for three patients.