LinearModel

class LinearModel(*args)

The linear model class is created through the method build of a LinearModelFactory.

Attributes
thisown

The membership flag

Methods

getClassName()

Accessor to the object’s name.

getConfidenceIntervals()

Accessor to the confidence intervals.

getId()

Accessor to the object’s id.

getName()

Accessor to the object’s name.

getPValues()

Accessor to the p-values.

getPredicted(predictor)

Accessor to the evaluation function of linear model.

getRegression()

Accessor to the regression coefficients.

getResidual(predictor, measured)

Accessor to the residuals.

getShadowedId()

Accessor to the object’s shadowed id.

getVisibility()

Accessor to the object’s visibility state.

hasName()

Test if the object is named.

hasVisibleName()

Test if the object has a distinguishable name.

setName(name)

Accessor to the object’s name.

setShadowedId(id)

Accessor to the object’s shadowed id.

setVisibility(visible)

Accessor to the object’s visibility state.

__init__(*args)

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

getClassName()

Accessor to the object’s name.

Returns
class_namestr

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

getConfidenceIntervals()

Accessor to the confidence intervals.

Returns
confIntervalInterval

The confidence intervals of the linear model coefficients, corresponding to the level precised when the LinearModel class has been created through the method build.

getId()

Accessor to the object’s id.

Returns
idint

Internal unique identifier.

getName()

Accessor to the object’s name.

Returns
namestr

The name of the object.

getPValues()

Accessor to the p-values.

Returns
pvaluescollection of Scalar

The collection of the p-values of the linear model coefficients.

getPredicted(predictor)

Accessor to the evaluation function of linear model.

Parameters
sampleX2-d sequence of float

The input sample to be evaluated by the linear model.

Returns
YSample

The response Y evaluated through the linear model on the sample sampleX.

getRegression()

Accessor to the regression coefficients.

Returns
coefPoint

The coefficients of the linear model: (a_0, a_1, \ldots, a_n).

getResidual(predictor, measured)

Accessor to the residuals.

Parameters
Xsample: 2-d sequence of float

The input sample on which the linear model has been built.

Ysample: 2-d sequence of float

The 1d output sample on which the linear model has been built.

Returns
residualSample

The residuals computed on each point.

getShadowedId()

Accessor to the object’s shadowed id.

Returns
idint

Internal unique identifier.

getVisibility()

Accessor to the object’s visibility state.

Returns
visiblebool

Visibility flag.

hasName()

Test if the object is named.

Returns
hasNamebool

True if the name is not empty.

hasVisibleName()

Test if the object has a distinguishable name.

Returns
hasVisibleNamebool

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

setName(name)

Accessor to the object’s name.

Parameters
namestr

The name of the object.

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters
idint

Internal unique identifier.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters
visiblebool

Visibility flag.

thisown

The membership flag