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scalation/scalation/scalation.modeling/scalation.modeling.forecasting/ARX_SR_D

ARX_SR_D

scalation.modeling.forecasting.ARX_SR_D
See theARX_SR_D companion class
object ARX_SR_D extends MakeMatrix4TS

The ARX_SR_D companion object provides factory methods for the ARX_SR_D class.

Attributes

Companion
class
Graph
Supertypes
class Object
trait Matchable
class Any
Self type
ARX_SR_D.type

Members list

Value members

Concrete methods

def apply(xe: MatrixD, y: VectorD, hh: Int, fname_: Array[String] = ..., tRng: Range = ..., hparam: HyperParameter = ..., fEndo_enab: LinkedHashSet[TransformT] = ..., fExo_enab: Array[LinkedHashSet[TransformT]] = ..., bakcast: Boolean = ...): ARX_SR_D

Create an ARX_SR_D object by building an input matrix xy and then calling the ARX_SR_D constructor.

Create an ARX_SR_D object by building an input matrix xy and then calling the ARX_SR_D constructor.

Value parameters

bakcast

whether a backcasted value is prepended to the time series (defaults to false)

fEndo_enab

the set of transforms to be used for the endogenous

fExo_enab

the array containing the sets of transforms to be used for the exogenous

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

def formNames(n_exo: Int, hp_: HyperParameter, n_fEn: Int, n_fExArr: Array[Int]): Array[String]

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_fExArr

the number of functions used to map exogenous variables

Attributes

def rescale(xe: MatrixD, y: VectorD, hh: Int, fname_: Array[String] = ..., tRng: Range = ..., hparam: HyperParameter = ..., fEndo_enab: LinkedHashSet[TransformT] = ..., fExo_enab: Array[LinkedHashSet[TransformT]] = ..., bakcast: Boolean = ..., tFormT: TransformT = ...): ARX_SR_D

Create an ARX_SR_D object by building an input matrix xy and then calling the ARX_SR_D constructor, with rescaling of endogneous and exogenous variable values.

Create an ARX_SR_D object by building an input matrix xy and then calling the ARX_SR_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_enab

the set of transforms to be used for the endogenous

fExo_enab

the array containing the sets of transforms to be used for the exogenous

fname_

the feature/variable names

hh

the maximum forecasting horizon (h = 1 to hh)

hparam

the hyper-parameters

tFormT

the transform for rescaling endogenous and exogenous

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

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