# hmm.discnp v0.1-7

0

Monthly downloads

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 | |

sp | Calculate the conditional state probabilities. | |

pr | Probability of state sequences. | |

logLikHmm | Log likelihood of a hidden Markov model | |

hmm.discnp-internal | Internal hmm.discnp functions. | |

viterbi | Most probable state sequence. | |

mps | Most probable states. | |

sim.hmm | Simulate discrete data from a hidden Markov model. | |

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

hmm | Fit a hidden Markov model to discrete data. | |

No Results! |

## Last month downloads

## Details

Date | 2012-02-09 |

License | GPL (>= 2) |

URL | http://www.math.unb.ca/~rolf/ |

Packaged | 2012-02-09 02:17:56 UTC; rolf |

Repository | CRAN |

Date/Publication | 2012-02-09 08:07:27 |

depends | base (>= 0.99) , R (>= 0.99) |

Contributors | Limin Liu, Rolf Turner |

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