object TrigRegression extends ModelFactory
The TrigRegression companion object provides factory functions and functions
for creating functional forms.
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def
allForms(x: MatriD, ord: Int): MatriD
Create all forms/terms for each row/point placing them in a new matrix.
Create all forms/terms for each row/point placing them in a new matrix.
- x
the original un-expanded input/data matrix
- ord
the order (max degree) of the polynomial
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def
allForms(x: MatriD): MatriD
Create all forms/terms for each row/point placing them in a new matrix.
Create all forms/terms for each row/point placing them in a new matrix.
- x
the original un-expanded input/data matrix
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def
apply(x: MatriD, y: VectoD, ord: Int, fname: Strings, hparam: HyperParameter, technique: RegTechnique.RegTechnique): TrigRegression
Create a
TrigRegressionobject from a data matrix and a response vector.Create a
TrigRegressionobject from a data matrix and a response vector. This factory function provides data rescaling.- x
the initial data/input matrix (before polynomial term expansion)
- y
the response/output m-vector
- ord
the order (k) of the polynomial (max degree)
- 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
- See also
ModelFactory
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def
apply(t: VectoD, y: VectoD, ord: Int, fname: Strings, hparam: HyperParameter, technique: RegTechnique.RegTechnique): TrigRegression
Create a
TrigRegressionobject from a combined data-response matrix.Create a
TrigRegressionobject from a combined data-response matrix.- t
the initial data/input vector: t_i expands to x_i = [1, t_i, t_i2, ... t_ik]
- y
the response/ouput vector
- ord
the order (k) of the polynomial (max degree)
- hparam
the hyper-parameters
- technique
the technique used to solve for b in x.t*x*b = x.t*y
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def
apply(xy: MatriD, ord: Int, fname: Strings = null, hparam: HyperParameter = null, technique: RegTechnique.RegTechnique = Cholesky): TrigRegression
Create a
TrigRegressionobject from a combined data-response matrix.Create a
TrigRegressionobject from a combined data-response matrix.- xy
the initial combined data-response matrix (before polynomial term expansion)
- ord
the order (k) of the polynomial (max degree)
- hparam
the hyper-parameters
- technique
the technique used to solve for b in x.t*x*b = x.t*y
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- val drp: (Null, Null, RegTechnique.Value)
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def
forms(v: VectoD, k: Int, nt: Int, w: Double): VectoD
Given a 1-vector/point 'v', compute the values for all of its trigonmetric forms/terms, returning them as a vector.
Given a 1-vector/point 'v', compute the values for all of its trigonmetric forms/terms, returning them as a vector. '[1, sin (wt), cos (wt), sin (2wt), cos (2wt), ...]'.
- v
the vector/point (i-th row of t) for creating forms/terms
- k
number of features/predictor variables (not counting intercept) = 1
- nt
the number of terms
- w
the base displacement angle in radians
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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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def
numTerms(k: Int): Int
The number of terms/parameters in the model (assumes
Regressionwith intercept.The number of terms/parameters in the model (assumes
Regressionwith intercept. Override for expanded columns, e.g.,QuadRegression.- k
the number of features/predictor variables (not counting intercept)
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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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