Package edu.cmu.tetrad.data

Class CorrelationMatrix

java.lang.Object

edu.cmu.tetrad.data.CovarianceMatrix

edu.cmu.tetrad.data.CorrelationMatrix

All Implemented Interfaces:

DataModel, ICovarianceMatrix, KnowledgeTransferable, VariableSource, TetradSerializable, Serializable

public final class CorrelationMatrix
extends CovarianceMatrix

Stores a correlation matrix together with variable names and sample size; intended as a representation of a data set.

Version:

$Id: $Id

Author:

josephramsey

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
CorrelationMatrix(DataSet dataSet)	Constructs a new correlation matrix from the the given DataSet.
CorrelationMatrix(ICovarianceMatrix matrix)	Constructs a new correlation matrix using the covariances in the given covariance matrix.
CorrelationMatrix(List<Node> variables, Matrix matrix, int sampleSize)	Constructs a correlation matrix data set using the given information.

Method Summary

Modifier and Type	Method	Description
Matrix	getSelection(int[] rows, int[] cols)	Returns a submatrix based on the specified rows and columns.
CorrelationMatrix	getSubCorrMatrix(String[] submatrixVarNames)	getSubCorrMatrix.
static CorrelationMatrix	serializableInstance()	Generates a simple exemplar of this class to test serialization.
void	setMatrix(Matrix matrix)	Sets the covariance matrix.

Methods inherited from class edu.cmu.tetrad.data.CovarianceMatrix

clearSelection, copy, getDimension, getKnowledge, getMatrix, getName, getSampleSize, getSelectedVariableNames, getSize, getSubmatrix, getSubmatrix, getSubmatrix, getValue, getVariable, getVariableName, getVariableNames, getVariables, isContinuous, isDiscrete, isMixed, isSelected, isSingular, removeVariables, select, setKnowledge, setName, setSampleSize, setValue, setVariables, toString

Methods inherited from class java.lang.Object

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

Constructor Details

CorrelationMatrix

public CorrelationMatrix(ICovarianceMatrix matrix)

Constructs a new correlation matrix using the covariances in the given covariance matrix.

Parameters:

matrix - a ICovarianceMatrix object

CorrelationMatrix

public CorrelationMatrix(DataSet dataSet)

Constructs a new correlation matrix from the the given DataSet.

Parameters:

dataSet - a DataSet object

CorrelationMatrix

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

Constructs a correlation matrix data set using the given information. The matrix matrix is internally converted to a correlation matrix.

Parameters:

variables - a List object

matrix - a Matrix object

sampleSize - a int

Method Details

serializableInstance

public static CorrelationMatrix serializableInstance()

Generates a simple exemplar of this class to test serialization.

Returns:

a CorrelationMatrix object

setMatrix

public void setMatrix(Matrix matrix)

Sets the covariance matrix.

Specified by:

setMatrix in interface ICovarianceMatrix

Overrides:

setMatrix in class CovarianceMatrix

Parameters:

matrix - the matrix to set

getSelection

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

Returns a submatrix based on the specified rows and columns.

Specified by:

getSelection in interface ICovarianceMatrix

Overrides:

getSelection in class CovarianceMatrix

Parameters:

rows - an array of integers representing the row indices to be included in the selection.

cols - an array of integers representing the column indices to be included in the selection.

Returns:

a Matrix object containing the selected rows and columns.

getSubCorrMatrix

public CorrelationMatrix getSubCorrMatrix(String[] submatrixVarNames)

getSubCorrMatrix.

Parameters:

submatrixVarNames - an array of String objects

Returns:

a submatrix, returning as a correlation matrix, with variables in the given order.