The ARY_Quad companion object provides factory methods for the ARY_Quad class.
Attributes
Members list
Value members
Concrete methods
Create an ARY_Quad object by building an input matrix x and then calling the ARY_Quad constructor.
Create an ARY_Quad object by building an input matrix x and then calling the ARY_Quad constructor.
Value parameters
- bakcast
-
whether a backcasted value is prepended to the time series (defaults to false)
- fname_
-
the feature/variable names
- hh
-
the maximum forecasting horizon (h = 1 to hh)
- hparam
-
the hyper-parameters
- tRng
-
the time range, if relevant (time index may suffice)
- y
-
the response vector (time series data)
Attributes
Build the input matrix by combining the p + spec columns for the trend and endogenous variable with the q * xe.dim2 columns for the exogenous variables.
Build the input matrix by combining the p + spec columns for the trend and endogenous variable with the q * xe.dim2 columns for the exogenous variables.
Value parameters
- bakcast
-
whether a backcasted value is prepended to the time series (defaults to false)
- hp_
-
the hyper-parameters
- tForm
-
the z-transform (rescale to standard normal)
- y
-
the response vector (time series data)
Attributes
Create an ARY_Quad object by building an input matrix xy and then calling the ARY_Quad constructor. Also rescale the input data.
Create an ARY_Quad object by building an input matrix xy and then calling the ARY_Quad constructor. Also rescale the input data.
Value parameters
- bakcast
-
whether a backcasted value is prepended to the time series (defaults to false)
- hh
-
the maximum forecasting horizon (h = 1 to hh)
- hparam
-
the hyper-parameters
- tForm
-
the z-transform (rescale to standard normal)
- tRng
-
the time range, if relevant (time index may suffice)
- y
-
the endogenous/response vector (main time series data)