LinearModelAlgorithm

class LinearModelAlgorithm(*args)

Class used to create a linear model from numerical samples.

Available usages:

LinearModelAlgorithm(Xsample, Ysample)

LinearModelAlgorithm(Xsample, basis, Ysample)

Parameters
XSample2-d sequence of float

The input samples of a model.

YSample2-d sequence of float

The output samples of a model, must be of dimension 1.

basisBasis

The \phi basis .

See also

LinearModelResult

Notes

This class is used in order to create a linear model from data samples. The linear regression model between the scalar variable Y and the n -dimensional vector \vect{X} = (X_i)_{i \leq n} writes as follows:

\tilde{Y} = \sum_{i=0}^p a_i \phi_i(X) + \epsilon

where \epsilon is the residual, supposed to follow the standard Normal distribution, \phi a functional basis. The algorithm class enables to estimate the coefficients of the linear expansion.

If basis is not specified, the underlying model is :

\tilde{Y} = a_0 + \sum_{i=1}^n a_i X_i + \epsilon

The coefficients a_i are evaluated using a least squares method. Default

method is QR. User might choose also SVD or Cholesky (usefull if basis is orthogonal) and large dataset.

The evaluation of the coefficients is completed by some usefull parameters that could help the diagnostic of the linearity.

Methods

getBasis(self)

Accessor to the input basis.

getClassName(self)

Accessor to the object’s name.

getDistribution(self)

Accessor to the joint probability density function of the physical input vector.

getId(self)

Accessor to the object’s id.

getInputSample(self)

Accessor to the input sample.

getName(self)

Accessor to the object’s name.

getOutputSample(self)

Accessor to the output sample.

getResult(self)

Accessor to the computed linear model.

getShadowedId(self)

Accessor to the object’s shadowed id.

getVisibility(self)

Accessor to the object’s visibility state.

hasName(self)

Test if the object is named.

hasVisibleName(self)

Test if the object has a distinguishable name.

run(self)

Compute the response surfaces.

setDistribution(self, distribution)

Accessor to the joint probability density function of the physical input vector.

setName(self, name)

Accessor to the object’s name.

setShadowedId(self, id)

Accessor to the object’s shadowed id.

setVisibility(self, visible)

Accessor to the object’s visibility state.
__init__(self, \*args)

Initialize self. See help(type(self)) for accurate signature.

getBasis(self)

Accessor to the input basis.

Returns
basisBasis

The basis which had been passed to the constructor.

getClassName(self)

Accessor to the object’s name.

Returns
class_namestr

The object class name (object.__class__.__name__).

getDistribution(self)

Accessor to the joint probability density function of the physical input vector.

Returns
distributionDistribution

Joint probability density function of the physical input vector.

getId(self)

Accessor to the object’s id.

Returns
idint

Internal unique identifier.

getInputSample(self)

Accessor to the input sample.

Returns
inputSampleSample

The Xsample which had been passed to the constructor.

getName(self)

Accessor to the object’s name.

Returns
namestr

The name of the object.

getOutputSample(self)

Accessor to the output sample.

Returns
outputSampleSample

The Ysample which had been passed to the constructor.

getResult(self)

Accessor to the computed linear model.

Returns
resultLinearModelResult

The linear model built from numerical samples, along with other useful informations.

getShadowedId(self)

Accessor to the object’s shadowed id.

Returns
idint

Internal unique identifier.

getVisibility(self)

Accessor to the object’s visibility state.

Returns
visiblebool

Visibility flag.

hasName(self)

Test if the object is named.

Returns
hasNamebool

True if the name is not empty.

hasVisibleName(self)

Test if the object has a distinguishable name.

Returns
hasVisibleNamebool

True if the name is not empty and not the default one.

run(self)

Compute the response surfaces.

Notes

It computes the response surfaces and creates a MetaModelResult structure containing all the results.

setDistribution(self, distribution)

Accessor to the joint probability density function of the physical input vector.

Parameters
distributionDistribution

Joint probability density function of the physical input vector.

setName(self, name)

Accessor to the object’s name.

Parameters
namestr

The name of the object.

setShadowedId(self, id)

Accessor to the object’s shadowed id.

Parameters
idint

Internal unique identifier.

setVisibility(self, visible)

Accessor to the object’s visibility state.

Parameters
visiblebool

Visibility flag.