View source: R/specification.R

issm_modelspec | R Documentation |

Specifies an ISSM model prior to estimation.

issm_modelspec( y, slope = TRUE, slope_damped = FALSE, seasonal = FALSE, seasonal_frequency = 1, seasonal_type = c("trigonometric", "regular"), seasonal_harmonics = NULL, ar = 0, ma = 0, xreg = NULL, transformation = "box-cox", lambda = 1, lower = 0, upper = 1, sampling = NULL, ... )

`y` |
an xts vector. |

`slope` |
(Logical) slope component. |

`slope_damped` |
(Logical) slope dampening component. |

`seasonal` |
(Logical) seasonal component(s). |

`seasonal_frequency` |
vector of numeric seasonal frequencies. For trigonometric this can be fractional, but must be integer for regular seasonality. |

`seasonal_type` |
either trigonometric or regular. The latter currently does not allow multiple seasonality. |

`seasonal_harmonics` |
the number of harmonics per seasonal frequency for the trigonometric type. |

`ar` |
AR order. |

`ma` |
MA order. |

`xreg` |
an xts matrix of external regressors. |

`transformation` |
a valid transformation for y from the “tstransform” function in the “tsaux” package (currently box-cox or logit are available). |

`lambda` |
the Box Cox lambda. If not NULL, then either a numeric value or NA denoting automatic calculation. |

`lower` |
lower bound for the transformation. |

`upper` |
upper bound for the transformation. |

`sampling` |
(optional) sampling frequency of the dataset. If NULL, will try to identify from the timestamps of y. This is useful for plotting and extending the timestamps in the prediction horizon. |

`...` |
not used. |

The specification object holds the information and data which is then passed to the maximum likelihood estimation routines.

The specification performs some sanity checks on the arguments provided and sets up the required state space matrices and parameters which are used in the estimation stage.

An object of class “tsissm.spec” with the following slots:

`target` |
A list with original data series, the data series index and the sampling frequency |

`slope` |
A list with details about the slope state |

`seasonal` |
A list with details about the seasonal state |

`xreg` |
A list with details on the external regressors |

`transform` |
A list with details on the transformation |

`arma` |
A list with details on the ARMA state |

`S` |
A data.table with the vectorized state matrices |

`dims` |
A vector with dimensions and flags used in the estimation code |

`parmatrix` |
A data.table of the model parameters |

`idmatrix` |
A matrix with index information on the parameters |

De Livera, Alysha M and Hyndman, Rob J and Snyder, Ralph D, 2011,
Forecasting time series with complex seasonal patterns using exponential smoothing,
*Journal of the American Statistical Association*, **106(496)**, 1513–1527.

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