Companion object for class SARIMA. Includes features related to differencing and automated order selection.
Attributes
Members list
Value members
Concrete methods
Difference the time series. Return both the completely differenced time series and the intermediate (differenced once) time series (needed to scale back results later).
Difference the time series. Return both the completely differenced time series and the intermediate (differenced once) time series (needed to scale back results later).
Value parameters
- d
-
the order of simple differencing
- dd
-
the order of seasonal differencing
- period
-
the seasonal period
- y
-
the time series to be differenced
Attributes
Difference for seasonality.
Difference for seasonality.
Value parameters
- dd
-
the order of seasonal differencing
- period
-
the seasonal period
- y_
-
the time series to be seasonally differenced, this is usually the intermediate result after simple differencing.
Attributes
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.
Value parameters
- d
-
the order of simple differencing
- dd
-
the order of seasonal differencing
- period
-
the seasonal period
- x_
-
the intermediate result after differencing for trend, but before differencing for seasonality
- xp
-
the vector of predictions/fitted values of a differenced time series
- y
-
the original time series
Attributes
- See also
-
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
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.
Value parameters
- d
-
the order of simple differencing
- dd
-
the order of seasonal differencing
- period
-
the seasonal period
- t
-
the time being forecasted (@see the forecast method)
- x_
-
the intermediate result after differencing for trend, but before differencing for seasonality
- xf
-
the vector of forecasted values of a differenced time series
- xx
-
the original zero-mean time series
Attributes
- See also
-
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
Transform the forecast values of a differenced time series back to the original scale. Undo seasonal differencing only.
Transform the forecast values of a differenced time series back to the original scale. Undo seasonal differencing only.
Value parameters
- dd
-
the order of seasonal differencing
- period
-
the seasonal period
- t
-
the time point being forecasted (@see the forecast method)
- x_
-
the intermediate result after differencing for trend, but before differencing for seasonality
- xf
-
the vector of forecasted values of a differenced time series
Attributes
- See also
-
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima
Transform the fitted values on the training data of a differenced time series back to the original scale. Undo seasonal differencing only.
Transform the fitted values on the training data of a differenced time series back to the original scale. Undo seasonal differencing only.
Value parameters
- dd
-
the order of seasonal differencing
- period
-
the seasonal period
- x_
-
the intermediate result after differencing for trend, but before differencing for seasonality
- xp
-
the vector of predictions/fitted values of a differenced time series
Attributes
- See also
-
stats.stackexchange.com/questions/32634/difference-time-series-before-arima-or-within-arima