Description Usage Arguments Author(s) See Also Examples

A Mixture Transition Distribution model (`march.Mtd`

) object of order *order* is constructed
according to a given `march.Dataset`

*y*. The first *maxOrder*-*order*
elements of each sequence are truncated in order to return a model
which can be compared with other Markovian models of visible order maxOrder.

1 2 | ```
march.mtd.construct(y, order, maxOrder = order, mtdg = FALSE,
init = "best", deltaStop = 1e-04, llStop = 0.01, maxIter = 0)
``` |

`y` |
the dataset ( |

`order` |
the order of the constructed model. |

`maxOrder` |
the maximum visible order among the set of Markovian models to compare. |

`mtdg` |
flag indicating whether the constructed model should be a MTDg using a different transition matrix for each lag (value: |

`init` |
the init method, to choose among |

`deltaStop` |
the delta below which the optimization phases of phi and Q stop. |

`llStop` |
the ll increase below which the EM algorithm stop. |

`maxIter` |
the maximal number of iterations of the optimisation algorithm (zero for no maximal number). |

Ogier Maitre

`march.Mtd-class`

, `march.Model-class`

, `march.Dataset-class`

.

1 2 3 4 5 6 7 | ```
# Build a 4th order MTD model from the pewee data set.
model <- march.mtd.construct(pewee,4)
print(model)
# Build a 3th order MTDg model from the pewee data set.
model <- march.mtd.construct(pewee,3,mtdg=TRUE)
print(model)
``` |

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