object Regression4TS extends ModelFactory
The Regression4TS companion object provides factory functions and functions
for creating functional forms.
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- def allForms(x: MatriD, lag1: Int, lag2: Int, addOne: Boolean = false): MatriD
Create all forms/terms by concatenating columnwise the data matrix with lags 'lag1' to 'lag2', where 'lag1 = 0' is current values.
Create all forms/terms by concatenating columnwise the data matrix with lags 'lag1' to 'lag2', where 'lag1 = 0' is current values. Note 'allForms (x) = allForms (x, 0, 2)'
- x
the original un-expanded input/data matrix
- lag1
the first lag included (inclusive)
- lag2
the last lag included (inclusive)
- addOne
whether to add a column of all ones to the matrix (intercept)
- def allForms(x: MatriD): MatriD
Create all forms/terms by concatenating columnwise the data matrix with its first lag.
Create all forms/terms by concatenating columnwise the data matrix with its first lag.
- x
the original un-expanded input/data matrix
- Definition Classes
- Regression4TS → ModelFactory
- def allForms_xy(x: MatriD, y: VectoD, lag1: Int, lag2: Int, addOne: Boolean = false): MatriD
Create all forms/terms by concatenating columnwise the data matrix with lags 'lag1' to 'lag2', where 'lag1 = 0' is current values.
Create all forms/terms by concatenating columnwise the data matrix with lags 'lag1' to 'lag2', where 'lag1 = 0' is current values. Include lags for the response variable as well.
- x
the original un-expanded input/data matrix
- y
the original un-expanded output/response vector
- lag1
the first lag included (inclusive)
- lag2
the last lag included (inclusive)
- addOne
whether to add a column of all ones to the matrix (intercept)
- def allForms_y(y: VectoD, lag1: Int, lag2: Int, addOne: Boolean = false): MatriD
Create all forms/terms by concatenating columnwise the response vector lags 'lag1' to 'lag2', where 'lag1 = 0' is current values.
Create all forms/terms by concatenating columnwise the response vector lags 'lag1' to 'lag2', where 'lag1 = 0' is current values.
- y
the original un-expanded output/response vector
- lag1
the first lag included (inclusive) required to be > 0
- lag2
the last lag included (inclusive)
- addOne
whether to add a column of all ones to the matrix (intercept)
- def allForms_y_dir(y: VectoD, lag1: Int, lag2: Int, h: Int, addOne: Boolean = false): MatriD
Create all forms/terms by concatenating columnwise the response vector lags 'lag1' to 'lag2', where 'lag1 = 0' is current values.
Create all forms/terms by concatenating columnwise the response vector lags 'lag1' to 'lag2', where 'lag1 = 0' is current values. This method is used for the direct forecasting method, where the model is explictly trained for an 'h'-step ahead forecast.
- y
the original un-expanded output/response vector
- lag1
the first lag included (inclusive) required to be > 0
- lag2
the last lag included (inclusive)
- h
the forecasting horizon for the model to be trained on.
- addOne
whether to add a column of all ones to the matrix (intercept)
- See also
arxiv.org/pdf/1108.3259.pdf
- def apply(x: MatriD, y: VectoD, fname: Strings, hparam: HyperParameter, technique: RegTechnique.RegTechnique, addOne: Boolean): Regression4TS
Create a
Regression4TSobject from a data matrix and a response vector.Create a
Regression4TSobject from a data matrix and a response vector. This factory function provides data rescaling.- x
the initial data/input matrix (before quadratic term expansion)
- y
the response/output m-vector
- fname
the feature/variable names (use null for default)
- hparam
the hyper-parameters (use null for default)
- technique
the technique used to solve for b in x.t*x*b = x.t*y (use OR for default)
- addOne
whether to add a column of all ones to the data matrix
- See also
ModelFactory
- def apply(xy: MatriD, fname: Strings = null, hparam: HyperParameter = hp, technique: RegTechnique.RegTechnique = QR, addOne: Boolean = true): Regression4TS
Create a
Regression4TSobject from a combined data-response matrix.Create a
Regression4TSobject from a combined data-response matrix.- xy
the initial combined data-response matrix (before quadratic term expansion)
- hparam
the hyper-parameters
- technique
the technique used to solve for b in x.t*x*b = x.t*y
- addOne
whether to add a column of all ones to the data matrix
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- def forms(xi: VectoD, k: Int, nt: Int): VectoD
Given a vector/point 'v', compute the values for all of its forms/terms, returning them as a vector (assumes
Regressionwith intercept).Given a vector/point 'v', compute the values for all of its forms/terms, returning them as a vector (assumes
Regressionwith intercept). Override for expanded columns, e.g.,QuadRegression.- xi
the vector/point (i-th row of x) for creating forms/terms
- k
the number of features/predictor variables (not counting intercept)
- nt
the number of terms
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- val hp: HyperParameter
Base hyper-parameter specification for
Regression4TS - final def isInstanceOf[T0]: Boolean
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- def numTerms(k: Int): Int
The number of terms include current value and lag one value.
The number of terms include current value and lag one value. when there are no cross-terms.
- k
number of features/predictor variables (not counting intercept)
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- Regression4TS → ModelFactory
- val rescale: Boolean
The 'rescale' flag indicated whether the data is to be rescaled/normalized
The 'rescale' flag indicated whether the data is to be rescaled/normalized
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- def rescaleOff(): Unit
Turn rescaling off.
Turn rescaling off.
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- def rescaleOn(): Unit
Turn rescaling on.
Turn rescaling on.
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