The ARY companion object provides factory methods for the ARY class.
Attributes
Members list
Value members
Concrete methods
Create an ARY object by making/building an input matrix x and then calling the ARY constructor.
Create an ARY object by making/building an input matrix x and then calling the ARY 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
Create an ARY object for the special case of ARY(1) and use SimpleRegression.
Create an ARY object for the special case of ARY(1) and use SimpleRegression.
Value parameters
- 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
- y
-
the response vector (time series data)
Attributes
Create an ARY object by building an input matrix xy and then calling the ARY constructor. Also rescale the input data.
Create an ARY object by building an input matrix xy and then calling the ARY 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)