fit an AR model for each class of C by maximum likelihood method.

1 | ```
Mstep.classif(data, C, order)
``` |

`data` |
array of univariate or multivariate series with dimension T*N.samples*d. T: number of time steps of each sample, N.samples: number of realisations of the same stationary process, d: dimension. |

`C` |
Class sequence |

`order` |
order of AR models (all models will have the same order) |

list containing

`A0` |
intercept |

`A` |
AR coefficients |

`sigma` |
variance of innovation |

`LL` |
log likelihood |

Valerie Monbet, valerie.monbet@univ-rennes1.fr

fit.MSAR

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Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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