Description Usage Arguments Value References Examples

Function used to generate a hidden Markov model with discrete observations and random parameters. This model is used when the observed data are counts that can be modelled with a mixture of Poissons. The code for the methods with categorical values or continuous data can be viewed in `"initHMM"`

and `"initGHMM"`

, respectively.

1 | ```
initPHMM(n)
``` |

`n` |
the number of hidden states to use. |

A `"list"`

that contains all the required values to specify the model.

`Model` |
it specifies that the observed values are to be modeled as a Poisson mixture model. |

`StateNames` |
the set of hidden state names. |

`A` |
the transition probabilities matrix. |

`B` |
a vector with the lambda parameter for each Poisson distribution. |

`Pi` |
the initial probability vector. |

Cited references are listed on the RcppHMM manual page.

1 2 3 |

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