object ARIMA
Companion object for class ARIMA. 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(y: VectoD, d: Int): VectoD
Return the 'd'th difference of the time-series for 'd' in {0, 1, 2, 3}.
Return the 'd'th difference of the time-series for 'd' in {0, 1, 2, 3}. A new vector is returned even when there is no difference taken ('d = 0'), to ensure the original is preserved.
- y
the original time-series to be differenced
- d
the order of simple differencing
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def
transformBack(yp: VectoD, y: 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.
- yp
the vector of predicted/fitted values
- y
the original time-series vector
- 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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def
transformBackF(yf: VectoD, y: 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.
- yf
the vector of forecasted values
- y
the original time series
- d
the order of simple differencing
- t
the time point being forecasted (@see the 'forecast' method)
- See also
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
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def
transformBack_allH(ypa: MatriD, y: VectoD, d: Int): MatriD
Transform the forecasted values of a differenced time series back to the original for all horizons scale.
Transform the forecasted values of a differenced time series back to the original for all horizons scale.
- ypa
the matrix of all multi-horizon forecasted values
- y
the original time-series vector
- d
the order of simple differencing
- See also
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima