This program makes a local linear ansatz and estimates the one step prediction error of the model. The difference to lfo-test is that it does it as a function of the neighborhood size (see Casdagli).

**lfo-ar** means something like **local-first-order -› AR-model**

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 points to use | whole file |

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

-c# | column to be read | 1 |

-m#,# | # of components, embedding dimension | 1,2 |

-d# | delay for the embedding | 1 |

-i# | for how many points should the error be calculated | all |

-r# | neighborhood size to start with | (data interval)/1000 |

-R# | neighborhood size to end with | data interval |

-f# | factor to increase the neighborhood size if not enough neighbors were found | 1.2 |

-s# | steps to be forecasted (x_{n+steps}=f(\vec{x}_n)) | 1 |

-C# | width of causality window | steps to be forecasted |

-o[#] | output file name | without filename 'datafile.ll' (or stdin.ll if stdin was read) with no -o given, stdout is used |

-V# | verbosity level 0: only panic messages 1: add input/output messages | 1 |

-h | show these options | none |

- neighborhood size (units of the data)
- relative forecast error ((forecast error)/(variance of the data))
- fraction of points for which neighbors were found for this neighborhood size
- average number of neighbors found per point
- variance of the fraction of points for which neighbors were found

View the C-sources.

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