This program fits (by means of least squares) an autoregressive integrated moving average (ARIMA) model to the possibly multivariate data.

As a first step a AR model is fitted to give a first guess of the residuals which enter the MA part. With these residuals the full ARIMA is fitted. This fit is repeated until convergence of the residuals is reached or a maximum number of iterations was performed.

Note that no attempt has been made to generate a

Everything not being a valid option will be interpreted as a potential datafile name. Given no datafile at all, means read stdin. Also - means stdin

Possible options are:

Option | Description | Default |
---|---|---|

-l# | number of data to use | whole file |

-x# | number of lines to be ignored | 0 |

-m# | dimension of the vectors | 1 |

-c# | column to be read | 1,...,dimension of the vectors |

-p# | order of the initial AR-model | 10 |

-P# | order of the AR,I,MA model | 0,0,0 (means it just does the initial AR Modeling) |

-I# | max. number of iterations of the ARIMA Fit | 50 |

-e# | required accuracy of the ARIMA convergence | 0.001 |

-s# | length of iterated data set | no iteration |

-o# | output file name | without file name: 'datafile'.ari (or stdin.ari if stdin was used) if no -o is given stdout is used |

-V# | verbosity level 0: only panic messages 1: add input/output messages 2: print residuals though iterating a model 4: print original data + residuals | 1 |

-h | show these options | none |

The first line contains the forecast error averaged over all components. The second line contains the average forecast errors for all components individually. The third line contains the Log-likelihood and the AIC values of the fit. The next p*m lines contain the fitted ar coefficients and the rest of the file are either the residuals of the fit or a simulated new trajectory.

If P is given:

The first lines (marked #iteration xxx) show the convergence of the
residuals of the ARIMA fit. The rest of the files is like in the above
case.

View the C-sources

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