Package edu.cmu.tetrad.sem

Class SemEstimator

java.lang.Object

edu.cmu.tetrad.sem.SemEstimator

All Implemented Interfaces:

TetradSerializable, Serializable

public final class SemEstimator
extends Object
implements TetradSerializable

Estimates a SemIm given a CovarianceMatrix and a SemPm. (A DataSet may be substituted for the CovarianceMatrix.)

Author:

Frank Wimberly, Ricardo Silva, Don Crimbchin, Joseph Ramsey

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
SemEstimator(DataSet dataSet, SemPm semPm)	Constructs a Sem Estimator that does default estimation.
SemEstimator(DataSet dataSet, SemPm semPm, SemOptimizer semOptimizer)	Constructs a new SemEstimator that uses the specified optimizer.
SemEstimator(ICovarianceMatrix covMatrix, SemPm semPm)	Constructs a SEM estimator that does default estimation.
SemEstimator(ICovarianceMatrix covMatrix, SemPm semPm, SemOptimizer semOptimizer)	Constructs a new SemEstimator that uses the specified optimizer.

Method Summary

Modifier and Type	Method	Description
SemIm	estimate()	Runs the estimator on the data and SemPm passed in through the constructor.
ICovarianceMatrix	getCovMatrix()
DataSet	getDataSet()
SemIm	getEstimatedSem()
SemPm	getSemPm()
static SemEstimator	serializableInstance()	Generates a simple exemplar of this class to test serialization.
void	setNumRestarts(int numRestarts)
void	setScoreType(ScoreType scoreType)
void	setSemOptimizer(SemOptimizer semOptimizer)
String	toString()

Methods inherited from class java.lang.Object

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

Constructor Details

SemEstimator

public SemEstimator(DataSet dataSet,
 SemPm semPm)

Constructs a Sem Estimator that does default estimation.

Parameters:

semPm - a SemPm specifying the graph and parameterization for the model.

dataSet - a DataSet, all of whose variables are contained in the given SemPm. (They are identified by name.)

SemEstimator

public SemEstimator(ICovarianceMatrix covMatrix,
 SemPm semPm)

Constructs a SEM estimator that does default estimation.

Parameters:

semPm - a SemPm specifying the graph and parameterization for the model.

covMatrix - a CovarianceMatrix, all of whose variables are contained in the given SemPm. (They are identified by name.)

SemEstimator

public SemEstimator(DataSet dataSet,
 SemPm semPm,
 SemOptimizer semOptimizer)

Constructs a new SemEstimator that uses the specified optimizer.

Parameters:

semPm - a SemPm specifying the graph and parameterization for the model.

dataSet - a DataSet, all of whose variables are contained in the given SemPm. (They are identified by name.)

semOptimizer - the optimizer that optimizes the Sem.

SemEstimator

public SemEstimator(ICovarianceMatrix covMatrix,
 SemPm semPm,
 SemOptimizer semOptimizer)

Constructs a new SemEstimator that uses the specified optimizer.

Parameters:

semPm - a SemPm specifying the graph and parameterization for the model.

covMatrix - a covariance matrix, all of whose variables are contained in the given SemPm. (They are identified by name.)

semOptimizer - the optimizer that optimizes the Sem.

Method Details

serializableInstance

public static SemEstimator serializableInstance()

Generates a simple exemplar of this class to test serialization.

estimate

public SemIm estimate()

Runs the estimator on the data and SemPm passed in through the constructor.

getEstimatedSem

public SemIm getEstimatedSem()

Returns:

the estimated SemIm. If the estimate method has not yet been called, null is returned.

getDataSet

public DataSet getDataSet()

getSemPm

public SemPm getSemPm()

getCovMatrix

public ICovarianceMatrix getCovMatrix()

toString

public String toString()

Overrides:

toString in class Object

Returns:

a string representation of the Sem.

setSemOptimizer

public void setSemOptimizer(SemOptimizer semOptimizer)

setScoreType

public void setScoreType(ScoreType scoreType)

setNumRestarts

public void setNumRestarts(int numRestarts)