Package edu.cmu.tetrad.data

Class CovarianceMatrix

java.lang.Object

edu.cmu.tetrad.data.CovarianceMatrix

All Implemented Interfaces:

DataModel, ICovarianceMatrix, KnowledgeTransferable, VariableSource, TetradSerializable, Serializable

Direct Known Subclasses:

CorrelationMatrix

public class CovarianceMatrix
extends Object
implements ICovarianceMatrix

Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set. When constructed from a continuous data set, the matrix is not checked for positive definiteness; however, when a covariance matrix is supplied, its positive definiteness is always checked. If the sample size is less than the number of variables, the positive definiteness is "spot-checked"--that is, checked for various submatrices.

Author:

josephramsey

See Also:

• CorrelationMatrix
• Serialized Form

Constructor Summary

Constructors

Constructor	Description
CovarianceMatrix(CovarianceMatrix covMatrix)	Copy constructor.
CovarianceMatrix(DataSet dataSet)	Constructs a new covariance matrix from the given data set.
CovarianceMatrix(DataSet dataSet, boolean biasCorrected)
CovarianceMatrix(ICovarianceMatrix covMatrix)
CovarianceMatrix(List<Node> variables, double[][] matrix, int sampleSize)
CovarianceMatrix(List<Node> variables, Matrix matrix, int sampleSize)	Protected constructor to construct a new covariance matrix using the supplied continuous variables and the the given symmetric, positive definite matrix and sample size.

Method Summary

Modifier and Type	Method	Description
final void	clearSelection()
DataModel	copy()
final int	getDimension()
final Knowledge	getKnowledge()
final Matrix	getMatrix()
final String	getName()	Gets the name of the covariance matrix.
final int	getSampleSize()	The size of the sample used to calculated this covariance matrix.
final List<String>	getSelectedVariableNames()
Matrix	getSelection(int[] rows, int[] cols)
final int	getSize()
final ICovarianceMatrix	getSubmatrix(int[] indices)
final CovarianceMatrix	getSubmatrix(String[] submatrixVarNames)
final ICovarianceMatrix	getSubmatrix(List<String> submatrixVarNames)
final double	getValue(int i, int j)
Node	getVariable(String name)
final String	getVariableName(int index)
final List<String>	getVariableNames()	Returns the variable names associated with this getVariableNames.
final List<Node>	getVariables()	Returns the list of variables associated with this object.
boolean	isContinuous()
boolean	isDiscrete()
boolean	isMixed()
final boolean	isSelected(Node variable)
boolean	isSingular()
void	removeVariables(List<String> remaining)
final void	select(Node variable)
static ICovarianceMatrix	serializableInstance()	Generates a simple exemplar of this class to test serialization.
final void	setKnowledge(Knowledge knowledge)	Associates knowledge with this data.
void	setMatrix(Matrix matrix)
final void	setName(String name)	Sets the name of the covariance matrix.
final void	setSampleSize(int sampleSize)
void	setValue(int i, int j, double v)
void	setVariables(List<Node> variables)
final String	toString()	Prints out the matrix

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Details

CovarianceMatrix

public CovarianceMatrix(DataSet dataSet)

Constructs a new covariance matrix from the given data set.

Throws:

IllegalArgumentException - if this is not a continuous data set.

CovarianceMatrix

public CovarianceMatrix(DataSet dataSet,
 boolean biasCorrected)

CovarianceMatrix

public CovarianceMatrix(List<Node> variables,
 Matrix matrix,
 int sampleSize)

Protected constructor to construct a new covariance matrix using the supplied continuous variables and the the given symmetric, positive definite matrix and sample size. The number of variables must equal the dimension of the array.

Parameters:

variables - the list of variables (in order) for the covariance matrix.

matrix - an square array of containing covariances.

sampleSize - the sample size of the data for these covariances.

Throws:

IllegalArgumentException - if the given matrix is not symmetric (to a tolerance of 1.e-5) and positive definite, if the number of variables does not equal the dimension of m, or if the sample size is not positive.

CovarianceMatrix

public CovarianceMatrix(List<Node> variables,
 double[][] matrix,
 int sampleSize)

CovarianceMatrix

public CovarianceMatrix(CovarianceMatrix covMatrix)

Copy constructor.

CovarianceMatrix

public CovarianceMatrix(ICovarianceMatrix covMatrix)

Method Details

serializableInstance

public static ICovarianceMatrix serializableInstance()

Generates a simple exemplar of this class to test serialization.

getVariables

public final List<Node> getVariables()

Description copied from interface: VariableSource

Returns the list of variables associated with this object.

Specified by:

getVariables in interface ICovarianceMatrix

Specified by:

getVariables in interface VariableSource

Returns:

the list of variables (unmodifiable).

setVariables

public void setVariables(List<Node> variables)

Specified by:

setVariables in interface ICovarianceMatrix

getVariableNames

public final List<String> getVariableNames()

Description copied from interface: VariableSource

Returns the variable names associated with this getVariableNames.

Specified by:

getVariableNames in interface ICovarianceMatrix

Specified by:

getVariableNames in interface VariableSource

Returns:

the variable names, in order.

getVariableName

public final String getVariableName(int index)

Specified by:

getVariableName in interface ICovarianceMatrix

Returns:

the variable name at the given index.

getDimension

public final int getDimension()

Specified by:

getDimension in interface ICovarianceMatrix

Returns:

the dimension of the covariance matrix.

getSampleSize

public final int getSampleSize()

The size of the sample used to calculated this covariance matrix.

Specified by:

getSampleSize in interface ICovarianceMatrix

Returns:

The sample size (> 0).

setSampleSize

public final void setSampleSize(int sampleSize)

Specified by:

setSampleSize in interface ICovarianceMatrix

getName

public final String getName()

Gets the name of the covariance matrix.

Specified by:

getName in interface DataModel

Specified by:

getName in interface ICovarianceMatrix

Returns:

the name of the data model (may be null).

setName

public final void setName(String name)

Sets the name of the covariance matrix.

Specified by:

setName in interface DataModel

Specified by:

setName in interface ICovarianceMatrix

getKnowledge

public final Knowledge getKnowledge()

Specified by:

getKnowledge in interface ICovarianceMatrix

Specified by:

getKnowledge in interface KnowledgeTransferable

Returns:

the knowledge associated with this data.

setKnowledge

public final void setKnowledge(Knowledge knowledge)

Associates knowledge with this data.

Specified by:

setKnowledge in interface ICovarianceMatrix

Specified by:

setKnowledge in interface KnowledgeTransferable

getSubmatrix

public final ICovarianceMatrix getSubmatrix(int[] indices)

Specified by:

getSubmatrix in interface ICovarianceMatrix

Returns:

a submatrix of the covariance matrix with variables in the given order.

getSubmatrix

public final ICovarianceMatrix getSubmatrix(List<String> submatrixVarNames)

Specified by:

getSubmatrix in interface ICovarianceMatrix

getSubmatrix

public final CovarianceMatrix getSubmatrix(String[] submatrixVarNames)

Specified by:

getSubmatrix in interface ICovarianceMatrix

Returns:

a submatrix of this matrix, with variables in the given order.

getValue

public final double getValue(int i,
 int j)

Specified by:

getValue in interface ICovarianceMatrix

Returns:

the value of element (i,j) in the matrix

getSize

public final int getSize()

Specified by:

getSize in interface ICovarianceMatrix

Returns:

the size of the square matrix.

getMatrix

public final Matrix getMatrix()

Specified by:

getMatrix in interface ICovarianceMatrix

Returns:

a the covariance matrix (not a copy).

setMatrix

public void setMatrix(Matrix matrix)

Specified by:

setMatrix in interface ICovarianceMatrix

select

public final void select(Node variable)

Specified by:

select in interface ICovarianceMatrix

clearSelection

public final void clearSelection()

Specified by:

clearSelection in interface ICovarianceMatrix

isSelected

public final boolean isSelected(Node variable)

Specified by:

isSelected in interface ICovarianceMatrix

getSelectedVariableNames

public final List<String> getSelectedVariableNames()

Specified by:

getSelectedVariableNames in interface ICovarianceMatrix

toString

public final String toString()

Prints out the matrix

Specified by:

toString in interface DataModel

Specified by:

toString in interface ICovarianceMatrix

Overrides:

toString in class Object

isContinuous

public boolean isContinuous()

Specified by:

isContinuous in interface DataModel

isDiscrete

public boolean isDiscrete()

Specified by:

isDiscrete in interface DataModel

isMixed

public boolean isMixed()

Specified by:

isMixed in interface DataModel

getSelection

public Matrix getSelection(int[] rows,
 int[] cols)

Specified by:

getSelection in interface ICovarianceMatrix

getVariable

public Node getVariable(String name)

Specified by:

getVariable in interface DataModel

Specified by:

getVariable in interface ICovarianceMatrix

copy

public DataModel copy()

Specified by:

copy in interface DataModel

setValue

public void setValue(int i,
 int j,
 double v)

Specified by:

setValue in interface ICovarianceMatrix

removeVariables

public void removeVariables(List<String> remaining)

Specified by:

removeVariables in interface ICovarianceMatrix

isSingular

public boolean isSingular()