Package edu.cmu.tetrad.search.work_in_progress

Class IndTestFisherZRecursive

java.lang.Object

edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive

All Implemented Interfaces:

IndependenceTest

public final class IndTestFisherZRecursive
extends Object
implements IndependenceTest

Checks conditional independence of variable in a continuous data set using Fisher's Z test. See Spirtes, Glymour, and Scheines, "Causation, Prediction and Search," 2nd edition, page 94.

Version:

$Id: $Id

Author:

josephramsey, Frank Wimberly adapted IndTestCramerT for Fisher's Z

Constructor Summary

Constructors

Constructor	Description
IndTestFisherZRecursive(DataSet dataSet, double alpha)	Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous).
IndTestFisherZRecursive(ICovarianceMatrix covMatrix, double alpha)	Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
IndTestFisherZRecursive(Matrix data, List<Node> variables, double alpha)	Constructs a new Fisher Z independence test with the listed arguments.

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, Set<Node> z)	checkIndependence.
boolean	determines(Set<Node> _z, Node x)	Returns true if y is determined the variable in z.
double	getAlpha()	Gets the getModel significance level.
ICovarianceMatrix	getCov()	getCov.
DataSet	getData()	getData.
List<DataSet>	getDataSets()	Returns the datasets for this test
double	getPValue()	getPValue.
int	getSampleSize()	Returns the sample size.
Node	getVariable(String name)	Returns The variable by the given name.
List<Node>	getVariables()	Getter for the field variables.
IndependenceTest	indTestSubset(List<Node> vars)	Returns an Independence test for a sublist of the variables.
boolean	isVerbose()	isVerbose.
void	setAlpha(double alpha)	Sets the significance level.
void	setVariables(List<Node> variables)	Setter for the field variables.
void	setVerbose(boolean verbose)	Sets whether this test will print verbose output.
String	toString()	toString.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface edu.cmu.tetrad.search.IndependenceTest

checkIndependence, getVariableNames

Constructor Details

IndTestFisherZRecursive

public IndTestFisherZRecursive(DataSet dataSet,
 double alpha)

Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous). The given significance level is used.

Parameters:

dataSet - A data set containing only continuous columns.

alpha - The alpha level of the test.

IndTestFisherZRecursive

public IndTestFisherZRecursive(Matrix data,
 List<Node> variables,
 double alpha)

Constructs a new Fisher Z independence test with the listed arguments.

Parameters:

data - A 2D continuous data set with no missing values.

variables - A list of variables, a subset of the variables of data.

alpha - The significance cutoff level. p values less than alpha will be reported as dependent.

IndTestFisherZRecursive

public IndTestFisherZRecursive(ICovarianceMatrix covMatrix,
 double alpha)

Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.

Parameters:

covMatrix - a ICovarianceMatrix object

alpha - a double

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

Returns an Independence test for a sublist of the variables.

Creates a new independence test instance for a subset of the variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables.

Returns:

a IndependenceTest object

checkIndependence

public IndependenceResult checkIndependence(Node x,
 Node y,
 Set<Node> z)

checkIndependence.

Determines whether variable x is independent of variable y given a list of conditioning variables z.

Specified by:

checkIndependence in interface IndependenceTest

Parameters:

x - a Node object

y - a Node object

z - a Set object

Returns:

a IndependenceResult object

See Also:

• IndependenceResult

getPValue

public double getPValue()

getPValue.

Returns:

the probability associated with the most recently computed independence test.

getAlpha

public double getAlpha()

Gets the getModel significance level.

Specified by:

getAlpha in interface IndependenceTest

Returns:

a double

setAlpha

public void setAlpha(double alpha)

Sets the significance level.

Sets the significance level at which independence judgments should be made. Affects the cutoff for partial correlations to be considered statistically equal to zero.

Specified by:

setAlpha in interface IndependenceTest

Parameters:

alpha - This level.

getVariables

public List<Node> getVariables()

Getter for the field variables.

Specified by:

getVariables in interface IndependenceTest

Returns:

the list of variables over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.

setVariables

public void setVariables(List<Node> variables)

Setter for the field variables.

Parameters:

variables - a List object

getVariable

public Node getVariable(String name)

Returns The variable by the given name.

Specified by:

getVariable in interface IndependenceTest

Parameters:

name - a String object

Returns:

This variable.

determines

public boolean determines(Set<Node> _z,
 Node x)
                   throws UnsupportedOperationException

Returns true if y is determined the variable in z.

If isDeterminismAllowed(), deters to IndTestFisherZD; otherwise throws UnsupportedOperationException.

Specified by:

determines in interface IndependenceTest

Parameters:

_z - a Set object

x - a Node object

Returns:

True, if so.

Throws:

UnsupportedOperationException

getData

public DataSet getData()

getData.

Specified by:

getData in interface IndependenceTest

Returns:

the data set being analyzed.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

toString

public String toString()

toString.

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object

Returns:

a string representation of this test.

getCov

public ICovarianceMatrix getCov()

getCov.

Specified by:

getCov in interface IndependenceTest

Returns:

a ICovarianceMatrix object

getDataSets

public List<DataSet> getDataSets()

Returns the datasets for this test

Specified by:

getDataSets in interface IndependenceTest

Returns:

these datasets.

getSampleSize

public int getSampleSize()

Returns the sample size.

Specified by:

getSampleSize in interface IndependenceTest

Returns:

This size.

isVerbose

public boolean isVerbose()

isVerbose.

Specified by:

isVerbose in interface IndependenceTest

Returns:

a boolean

setVerbose

public void setVerbose(boolean verbose)

Sets whether this test will print verbose output.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True, if so.