object SARIMAX
Companion object for class SARIMAX
. Includes features related to differencing
and automated order selection.
- See also
www.jstatsoft.org/article/view/v027i03/v27i03.pdf
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- def difference(xx: VectoD, d: Int, dd: Int, period: Int): (VectoD, VectoD)
Difference the time series or external regressors.
Difference the time series or external regressors. Return both the completely differenced time series and the intermediate (differenced once) time series (needed to scale back results later).
- xx
the time series or external regressors to be differenced
- d
the order of simple differencing
- dd
the order of seasonal differencing
- period
the seasonal period
- def differenceSeason(x_: VectoD, dd: Int, period: Int): VectoD
Difference for seasonality.
Difference for seasonality.
- x_
the time series or external regressors to be seasonally differenced, this is usually the intermediate result after simple differencing.
- dd
the order of seasonal differencing
- period
the seasonal period
- def differenceTrend(xx: VectoD, d: Int): VectoD
Difference for trend.
Difference for trend.
- xx
the time series or external regressors to be trend differenced
- d
the order of simple differencing
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- def transformBack(xp: VectoD, x_: VectoD, xx: VectoD, d: Int, dd: Int, period: Int): VectoD
Transform the fitted values on the training data of a differenced time series back to the original scale.
Transform the fitted values on the training data of a differenced time series back to the original scale.
- xp
the vector of predictions/fitted values of a differenced time series
- x_
the intermediate result after differencing for trend, but before differencing for seasonality
- xx
the original zero-mean time series
- d
the order of simple differencing
- dd
the order of seasonal differencing
- period
the seasonal period
- See also
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
- def transformBackF(xf: VectoD, x_: VectoD, xx: VectoD, d: Int, dd: Int, period: Int, t: Int): VectoD
Transform the forecast values of a differenced time series back to the original scale.
Transform the forecast values of a differenced time series back to the original scale.
- xf
the vector of forecasted values of a differenced time series
- x_
the intermediate result after differencing for trend, but before differencing for seasonality
- xx
the original zero-mean time series
- d
the order of simple differencing
- dd
the order of seasonal differencing
- period
the seasonal period
- t
the time
- See also
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
- def transformBackFSeason(xf: VectoD, x_: VectoD, dd: Int, period: Int, t: Int): VectoD
Transform the forecast values of a differenced time series back to the original scale.
Transform the forecast values of a differenced time series back to the original scale. Undo seasonal differencing only.
- xf
the vector of forecasted values of a differenced time series
- x_
the intermediate result after differencing for trend, but before differencing for seasonality
- dd
the order of seasonal differencing
- period
the seasonal period
- See also
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
- def transformBackFTrend(xf_: VectoD, xx: VectoD, d: Int, t: Int): VectoD
Transform the forecast values of a differenced time series back to the original scale.
Transform the forecast values of a differenced time series back to the original scale. Undo trend differencing only.
- xf_
the vector of forecasted values after undoing seasonal differencing
- xx
the original zero-mean time series
- d
the order of simple differencing
- t
the time
- See also
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
- def transformBackSeason(xp: VectoD, x_: VectoD, dd: Int, period: Int): VectoD
Transform the fitted values on the training data of a differenced time series back to the original scale.
Transform the fitted values on the training data of a differenced time series back to the original scale. Undo seasonal differencing only.
- xp
the vector of predictions/fitted values of a differenced time series
- x_
the intermediate result after differencing for trend, but before differencing for seasonality
- dd
the order of seasonal differencing
- period
the seasonal period
- See also
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
- def transformBackTrend(xp_: VectoD, xx: VectoD, d: Int): VectoD
Transform the fitted values on the training data of a differenced time series back to the original scale.
Transform the fitted values on the training data of a differenced time series back to the original scale. Undo trend differencing only.
- xp_
the vector of predictions/fitted values after undoing seasonal differencing
- xx
the original zero-mean time series
- d
the order of simple differencing
- See also
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
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