object Regression_WLS
The Regression_WLS companion object provides methods for setting weights
and testing.
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def
reweightX(x: MatriD, rW: VectoD): MatriD
Reweight the data matrix 'x' by multiplying by the root weight 'rtW'.
Reweight the data matrix 'x' by multiplying by the root weight 'rtW'.
- x
the input/data m-by-n matrix
- rW
the root weight vector (rtW: either rootW or rW)
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def
reweightY(y: VectoD, rW: VectoD): VectoD
Reweight the response vector matrix 'y' by multiplying by the root weight 'rtW'.
Reweight the response vector matrix 'y' by multiplying by the root weight 'rtW'.
- y
the response vector
- rW
the root weight vector (rtW: either rootW or rW)
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def
setWeights(x: MatriD, y: VectoD, technique: RegTechnique.RegTechnique = QR, w0: VectoD = null): Unit
Estimate weights for the variables according to the reciprocal predicted rad's.
Estimate weights for the variables according to the reciprocal predicted rad's. Save the weight vector 'w' and root weight vector 'rootW' for the current model in companion object variables.
- x
the input/data m-by-n matrix
- y
the response vector
- technique
the technique used to solve for b in x.t*w*x*b = x.t*w*y
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def
setWeights0(x: MatriD, y: VectoD, technique: RegTechnique.RegTechnique = QR, w0: VectoD = null): Unit
Estimate weights for the variables according to the reciprocal actual rad's.
Estimate weights for the variables according to the reciprocal actual rad's. Save the weight vector 'w' and root weight vector 'rootW' for the current model in companion object variables.
- x
the input/data m-by-n matrix
- y
the response vector
- technique
the technique used to solve for b in x.t*w*x*b = x.t*w*y
- See also
'setWeights' that used predicted rad
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test(x: MatriD, y: VectoD, z: VectoD, w: VectoD = null): Unit
Test various regression techniques.
Test various regression techniques.
- x
the data matrix
- y
the response vector
- z
a vector to predict
- w
the root weights
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def
weights: VectoD
Return the weight vector for the current model.
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