These functions are deprecated and will ultimately be removed from the package. Please change to the object orientated versions: `BaumWelch`

, `residuals`

, `simulate`

or `Viterbi`

.

1 2 3 4 5 6 7 8 | ```
Baum.Welch(x, Pi, delta, distn, pm, pn = NULL, nonstat = TRUE,
maxiter = 500, tol = 1e-05, prt = TRUE,
posdiff = (distn[1]!="glm"))
residualshmm(x, Pi, delta, distn, pm, pn = NULL, discrete = FALSE)
sim.hmm(n, initial, Pi, distn, pm, pn = NULL)
sim.hmm1(n, initial, Pi, distn, pm)
sim.markov(n, initial, Pi)
Viterbihmm(x, Pi, delta, distn, pm, pn = NULL)
``` |

`x` |
is a vector of length |

`n` |
length of process. |

`initial` |
integer, being the initial hidden Markov state |

`Pi` |
is the |

`delta` |
is the marginal probability distribution of the |

`distn` |
is a character string with the distribution name, e.g. |

`pm` |
is a list object containing the (Markov dependent) parameter values associated with the distribution of the observed process (see |

`pn` |
is a list object containing the observation dependent parameter values associated with the distribution of the observed process (see |

`discrete` |
is logical, and is |

`nonstat` |
is logical, |

`maxiter` |
is the maximum number of iterations, default is 500. |

`tol` |
is the convergence criterion, being the difference between successive values of the log-likelihood; default is 0.00001. |

`prt` |
is logical, and determines whether information is printed at each iteration; default is |

`posdiff` |
is logical, and determines whether the iterative process stops if a negative log-likelihood difference occurs. |

The function `sim.hmm1`

will run faster for cases where the argument `pn`

is `NULL`

.

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