HSICEstimator

class HSICEstimator(*args)

Base class of HSIC estimators.

See also

HSICEstimatorConditionalSensitivity, HSICEstimatorGlobalSensitivity, HSICEstimatorTargetSensitivity

Notes

HSIC-based analyses must be performed by using the derived classes: HSICEstimatorConditionalSensitivity, HSICEstimatorGlobalSensitivity and HSICEstimatorTargetSensitivity.

Methods

drawHSICIndices()	Draw the HSIC indices.
drawPValuesPermutation()	Draw the p-values obtained by permutation.
drawR2HSICIndices()	Draw the R2-HSIC indices.
getClassName()	Accessor to the object's name.
getCovarianceModelCollection()	Get the list of all covariance models used.
getDimension()	Get the dimension of the input sample.
getEstimator()	Get the estimator used for computations.
getHSICIndices()	Get the HSIC indices.
getId()	Accessor to the object's id.
getImplementation()	Accessor to the underlying implementation.
getInputSample()	Get the input sample.
getName()	Accessor to the object's name.
getOutputSample()	Get the output sample.
getPValuesPermutation()	Get the p-value estimated through permutations.
getPermutationSize()	Get the number of permutations.
getR2HSICIndices()	Get the R2-HSIC indices.
getSize()	Get the size of the input sample.
setCovarianceModelCollection(coll)	Set the covariance models.
setInputSample(inputSample)	Set the input sample.
setName(name)	Accessor to the object's name.
setOutputSample(outputSample)	Set the output sample.
setPermutationSize(B)	Set the number of permutations to be used for p-value estimate.

__init__(*args)

drawHSICIndices()

Draw the HSIC indices.

Returns

graphGraph

The graph of all HSIC indices according to components.

drawPValuesPermutation()

Draw the p-values obtained by permutation.

Returns

graphGraph

The graph of all p-values by permutation according to components.

drawR2HSICIndices()

Draw the R2-HSIC indices.

Returns

graphGraph

The graph of all R2-HSIC indices according to components.

getClassName()

Accessor to the object’s name.

Returns

class_namestr

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

getCovarianceModelCollection()

Get the list of all covariance models used.

Returns

collCovarianceModelCollection

The list of all covariance models used. The last one is the output covariance model.

getDimension()

Get the dimension of the input sample.

Returns

dimint

The dimension of the input sample.

getEstimator()

Get the estimator used for computations.

Returns

estimatorHSICStat

The estimator used for internal computations.

getHSICIndices()

Get the HSIC indices.

Returns

hsicIndicesPoint

The HSIC indices of all components.

getId()

Accessor to the object’s id.

Returns

idint

Internal unique identifier.

getImplementation()

Accessor to the underlying implementation.

Returns

implImplementation

A copy of the underlying implementation object.

getInputSample()

Get the input sample.

Returns

inSampleSample

The input sample used for analysis.

getName()

Accessor to the object’s name.

Returns

namestr

The name of the object.

getOutputSample()

Get the output sample.

Returns

outSampleSample

The output sample used for analysis.

getPValuesPermutation()

Get the p-value estimated through permutations.

Returns

pvalPoint

The p-values of all components estimated with permutations of the data.

getPermutationSize()

Get the number of permutations.

Returns

permutationSizeint

The number of permutations.

getR2HSICIndices()

Get the R2-HSIC indices.

Returns

r2hsicIndicesPoint

The R2-HSIC indices of all components.

getSize()

Get the size of the input sample.

Returns

sizeint

The size of the input sample.

setCovarianceModelCollection(coll)

Set the covariance models.

Parameters

collCovarianceModelCollection

The list of all covariance models.

setInputSample(inputSample)

Set the input sample.

Parameters

inputSample2-d sequence of float

The input sample to be used.

setName(name)

Accessor to the object’s name.

Parameters

namestr

The name of the object.

setOutputSample(outputSample)

Set the output sample.

Parameters

outputSample2-d sequence of float

The output sample to be used.

setPermutationSize(B)

Set the number of permutations to be used for p-value estimate.

Parameters

Bint

The number of permutation used for p-value estimates.