The ARX_Symb_D companion object provides factory methods for the ARX_Symb_D class.
Attributes
- Companion
- class
- Graph
-
- Supertypes
- Self type
-
ARX_Symb_D.type
Members list
Value members
Concrete methods
Create an ARX_Symb_D object by building an input matrix xy and then calling the ARX_Symb_D constructor.
Create an ARX_Symb_D object by building an input matrix xy and then calling the ARX_Symb_D constructor.
Value parameters
- bakcast
-
whether a backcasted value is prepended to the time series (defaults to false)
- fEndo
-
the array of transforms used to transform endogenous variables
- fExo
-
the array of transforms used to transform exogenous variables
- 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)
- xe
-
the matrix of exogenous variable values
- y
-
the endogenous/response vector (main time series data)
Attributes
Form an array of names for the features included in the model.
Form an array of names for the features included in the model.
Value parameters
- hp_
-
the hyper-parameters
- n_exo
-
the number of exogenous variable
- n_fEn
-
the number of functions used to map endogenous variables
- n_fEx
-
the number of functions used to map exogenous variables
Attributes
Create an ARX_Symb_D object by building an input matrix xy and then calling the ARX_Symb_D constructor, with rescaling of endogneous and exogenous variable values.
Create an ARX_Symb_D object by building an input matrix xy and then calling the ARX_Symb_D constructor, with rescaling of endogneous and exogenous variable values.
Value parameters
- bakcast
-
whether a backcasted value is prepended to the time series (defaults to false)
- fEndo
-
the array of transforms used to transform endogenous variables
- fExo
-
the array of transforms used to transform exogenous variables
- fname_
-
the feature/variable names
- hh
-
the maximum forecasting horizon (h = 1 to hh)
- hparam
-
the hyper-parameters
- tForm
-
the transform for y
- tRng
-
the time range, if relevant (time index may suffice)
- xe
-
the matrix of exogenous variable values
- y
-
the endogenous/response vector (main time series data)