Package edu.cmu.tetrad.search.work_in_progress

Class IndTestPositiveCorr

java.lang.Object

edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr

All Implemented Interfaces:

IndependenceTest

public final class IndTestPositiveCorr
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
IndTestPositiveCorr(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).

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x0, Node y0, Set<Node> _z0)	Checks the independence between two nodes, given a set of conditioning nodes.
boolean	determines(List<Node> z, Node x)	Determines if there exists a causal relationship between the nodes in z and node x.
double	getAlpha()	Retrieves the alpha level of the Independence Test.
ICovarianceMatrix	getCov()	getCov.
DataSet	getData()	Retrieve the data set used in the independence test.
List<DataSet>	getDataSets()	Retrieves the data sets used in the independence test.
double	getPValue()	Calculates the p-value for the independence test.
int	getSampleSize()	Retrieves the sample size of the covariance matrix.
Node	getVariable(String name)	Retrieves the node associated with the given variable name.
List<Node>	getVariables()	Retrieves the list of variables used in the independence test.
IndependenceTest	indTestSubset(List<Node> vars)	Performs an independence test on a subset of variables.
boolean	isVerbose()	Returns whether the verbose mode is enabled.
void	setAlpha(double alpha)	Set the alpha level for the significance of the test.
void	setVariables(List<Node> variables)	Sets the variables used in the independence test.
void	setVerbose(boolean verbose)	Sets the verbose mode to either enabled or disabled.
String	toString()	Returns a string representation of the Fisher Z object.

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, determines, getVariableNames

Constructor Details

IndTestPositiveCorr

public IndTestPositiveCorr(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.

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

Performs an independence test on a subset of variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables.

Returns:

An IndependenceTest object representing the result of the test.

Throws:

UnsupportedOperationException - This method is not implemented and will always throw an UnsupportedOperationException.

checkIndependence

public IndependenceResult checkIndependence(Node x0,
 Node y0,
 Set<Node> _z0)

Checks the independence between two nodes, given a set of conditioning nodes.

Specified by:

checkIndependence in interface IndependenceTest

Parameters:

x0 - First node to check independence for.

y0 - Second node to check independence for.

_z0 - Set of conditioning nodes.

Returns:

An IndependenceResult object representing the result of the independence test.

See Also:

• IndependenceResult

getPValue

public double getPValue()

Calculates the p-value for the independence test.

Returns:

The p-value of the independence test.

getAlpha

public double getAlpha()

Retrieves the alpha level of the Independence Test.

Specified by:

getAlpha in interface IndependenceTest

Returns:

The alpha level.

setAlpha

public void setAlpha(double alpha)

Set the alpha level for the significance of the test.

Specified by:

setAlpha in interface IndependenceTest

Parameters:

alpha - The alpha level for the significance of the test. Must be a value between 0.0 and 1.0, inclusive.

Throws:

IllegalArgumentException - if the alpha value is out of range.

getVariables

public List<Node> getVariables()

Retrieves the list of variables used in the independence test.

Specified by:

getVariables in interface IndependenceTest

Returns:

The list of variables used in the independence test.

setVariables

public void setVariables(List<Node> variables)

Sets the variables used in the independence test.

Parameters:

variables - A list of Nodes representing the variables to be used in the test.

Throws:

IllegalArgumentException - if the number of variables is different from the current number of variables in the test.

getVariable

public Node getVariable(String name)

Retrieves the node associated with the given variable name.

Specified by:

getVariable in interface IndependenceTest

Parameters:

name - a String object representing the variable name.

Returns:

the node associated with the variable name.

determines

public boolean determines(List<Node> z,
 Node x)
                   throws UnsupportedOperationException

Determines if there exists a causal relationship between the nodes in z and node x.

Parameters:

z - The list of nodes representing the potential causes.

x - The node representing the potential effect.

Returns:

true if there exists a causal relationship between the nodes in z and node x, false otherwise.

Throws:

UnsupportedOperationException - if the method is not implemented.

getData

public DataSet getData()

Retrieve the data set used in the independence test.

Specified by:

getData in interface IndependenceTest

Returns:

The data set.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

toString

public String toString()

Returns a string representation of the Fisher Z object.

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object

Returns:

A string representation of the Fisher Z object.

getCov

public ICovarianceMatrix getCov()

getCov.

Specified by:

getCov in interface IndependenceTest

Returns:

a ICovarianceMatrix object

getDataSets

public List<DataSet> getDataSets()

Retrieves the data sets used in the independence test.

Specified by:

getDataSets in interface IndependenceTest

Returns:

A list of data sets.

getSampleSize

public int getSampleSize()

Retrieves the sample size of the covariance matrix.

Specified by:

getSampleSize in interface IndependenceTest

Returns:

The sample size.

isVerbose

public boolean isVerbose()

Returns whether the verbose mode is enabled.

Specified by:

isVerbose in interface IndependenceTest

Returns:

true if verbose mode is enabled, false otherwise.

setVerbose

public void setVerbose(boolean verbose)

Sets the verbose mode to either enabled or disabled.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True if verbose mode is enabled, false otherwise.