Time Series Analysis Using the Innovations Algorithm

aacvf | Autocovariance of ARMA model |

acvf | Autocovariance of data |

airpass | Number of international airline passengers, 1949 to 1960 |

arar | Forecast using ARAR algorithm |

ar.inf | Compute AR infinity coefficients |

arma | Estimate ARMA model coefficients using maximum likelihood |

autofit | Find the best model from a range of possible ARMA models |

burg | Estimate AR coefficients using the Burg method |

check | Check for causality and invertibility |

deaths | USA accidental deaths, 1973 to 1978 |

dowj | Dow Jones utilities index, August 28 to December 18, 1972 |

forecast | Forecast future values |

hannan | Estimate ARMA coefficients using the Hannan-Rissanen... |

hr | Estimate harmonic components |

ia | Estimate MA coefficients using the innovations algorithm |

itsmr-package | Time Series Analysis Using the Innovations Algorithm |

lake | Level of Lake Huron, 1875 to 1972 |

ma.inf | Compute MA infinity coefficients |

periodogram | Plot a periodogram |

plota | Plot data and/or model ACF and PACF |

plotc | Plot one or two time series |

plots | Plot spectrum of data or ARMA model |

Resid | Compute residuals |

season | Estimate seasonal component |

selftest | Run a self test |

sim | Generate synthetic observations |

smooth.exp | Apply an exponential filter |

smooth.fft | Apply a low pass filter |

smooth.ma | Apply a moving average filter |

smooth.rank | Apply a spectral filter |

specify | Specify an ARMA model |

strikes | USA union strikes, 1951-1980 |

Sunspots | Number of sunspots, 1770 to 1869 |

test | Test residuals for stationarity and randomness |

trend | Estimate trend component |

wine | Australian red wine sales, January 1980 to October 1991 |

yw | Estimate AR coefficients using the Yule-Walker method |

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