Genstat provides several methods for examining and analysing time series. Sample correlation functions are produced by the directive `CORRELATE`

:

`CORRELATE` |
forms correlations between variates, autocorrelations of variates, and lagged cross-correlations between variates |
---|

The analysis of Box-Jenkins models is specified by several directives:

`FTSM` |
forms preliminary estimates of parameters in time-series models |
---|---|

`TRANSFERFUNCTION` |
specifies input series and transfer-function models for subsequent estimation of a model for an output series |

`TFIT` |
estimates parameters in Box-Jenkins models for time series (renamed version of `ESTIMATE` , which is retained as a synonym) |

Information can be saved in Genstat data structures, or further output can be produced:

`TDISPLAY` |
displays further output after an analysis by `TFIT` |
---|---|

`TKEEP` |
saves results after an analysis by `TFIT` |

`TFORECAST` |
forecasts future values of a time series (renamed version of `FORECAST` , which is retained as a synonym) |

`TSUMMARIZE` |
displays characteristics of a time series model |

It is also possible to filter a time series, or perform spectral analysis via the Fourier transform of a time series using the directives:

`TFILTER` |
filters time series by time-series models (renamed version of `FILTER` , which is retained as a synonym) |
---|---|

`FOURIER` |
calculates cosine or Fourier transforms of a real or complex series |

Relevant procedures in the Library include:

`BJESTIMATE` |
fits an ARIMA model, with forecasts and residual checks |
---|---|

`BJFORECAST` |
plots forecasts of a time series using a previously fitted ARIMA |

`BJIDENTIFY` |
displays time series statistics useful for ARIMA model selection |

`DFOURIER` |
performs a harmonic analysis of a univariate time series |

`KALMAN` |
calculates estimates from the Kalman filter |

`DKALMAN` |
plots results from an analysis by `KALMAN` |

`MCROSSPECTRUM` |
performs a spectral analysis of a multiple time series |

`MC1PSTATIONARY` |
gives the stationary probabilities for a 1st-order Markov chain |

`MOVINGAVERAGE` |
calculates and plots the moving average of a time series |

`PERIODTEST` |
gives periodogram-based tests for white noise in time series |

`PREWHITEN` |
filters a time series before spectral analysis |

`REPPERIODOGRAM` |
gives periodogram-based analyses for replicated time series |

`SMOOTHSPECTRUM` |
forms smoothed spectrum estimates for univariate time series |

`TVARMA` |
fits a vector autoregressive moving average (VARMA) model |

`TVFORECAST` |
forecasts future values from a vector autoregressive moving average (VARMA) model |

`TVGRAPH` |
plots a vector autoregressive moving average (VARMA) model |