Package edu.cmu.tetrad.search

Class Cstar

java.lang.Object

edu.cmu.tetrad.search.Cstar

public class Cstar
extends Object

Implements the CStaR algorithm (Stekhoven et al., 2012), which finds a CPDAG of that data and then tries all orientations of the undirected edges about a variable in the CPDAG to estimate a minimum bound on the effect for a given edge. Some references include the following:

Stekhoven, D. J., Moraes, I., Sveinbjörnsson, G., Hennig, L., Maathuis, M. H., and Bühlmann, P. (2012). Causal stability ranking. Bioinformatics, 28(21), 2819-2823.

Meinshausen, N., and Bühlmann, P. (2010). Stability selection. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 72(4), 417-473.

Colombo, D., and Maathuis, M. H. (2014). Order-independent constraint-based causal structure learning. The Journal of Machine Learning Research, 15(1), 3741-3782.

This class is not configured to respect knowledge of forbidden and required edges.

Version:

$Id: $Id

Author:

josephramsey

See Also:

• Ida

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static enum	Cstar.CpdagAlgorithm	An enumeration of the options available for determining the CPDAG used for the algorithm.
static class	Cstar.Record	Represents a single record in the returned table for CSTaR.
static enum	Cstar.SampleStyle	An enumeration of the methods for selecting samples from the full dataset.

Constructor Summary

Constructors

Constructor	Description
Cstar(IndependenceWrapper test, ScoreWrapper score, Parameters parameters)	Constructor.

Method Summary

Modifier and Type	Method	Description
static LinkedList<Cstar.Record>	cStar(LinkedList<LinkedList<Cstar.Record>> allRecords)	Returns a list of records for making a CSTaR table.
File	getDir()	getDir.
LinkedList<LinkedList<Cstar.Record>>	getRecords(DataSet dataSet, List<Node> possibleCauses, List<Node> possibleEffects, int topBracket, String path)	Returns records for a set of variables with expected number of false positives bounded by q.
Graph	makeGraph(List<Cstar.Record> records)	Makes a graph of the estimated predictors to the effect.
String	makeTable(LinkedList<Cstar.Record> records)	Returns a text table from the given records
void	setCpdagAlgorithm(Cstar.CpdagAlgorithm cpdagAlgorithm)	The CSTaR algorithm can use any CPDAG algorithm; here you can set it.
void	setNumSubsamples(int numSubsamples)	Sets the number of subsamples.
void	setParallelized(boolean parallelized)	Sets whether the algorithm should be parallelized.
void	setSampleStyle(Cstar.SampleStyle sampleStyle)	Sets the sample style.
void	setSelectionAlpha(double selectionAlpha)	Sets the selection alpha.
void	setVerbose(boolean verbose)	Sets whether verbose output will be printed.

Methods inherited from class java.lang.Object

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

Constructor Details

Cstar

public Cstar(IndependenceWrapper test,
 ScoreWrapper score,
 Parameters parameters)

Constructor.

Parameters:

test - a IndependenceWrapper object

score - a ScoreWrapper object

parameters - a Parameters object

Method Details

cStar

public static LinkedList<Cstar.Record> cStar(LinkedList<LinkedList<Cstar.Record>> allRecords)

Returns a list of records for making a CSTaR table.

Parameters:

allRecords - the list of all records.

Returns:

The list for the CSTaR table.

setParallelized

public void setParallelized(boolean parallelized)

Sets whether the algorithm should be parallelized. Different runs of the algorithms can be run in different threads in parallel.

Parameters:

parallelized - True, if so.

getRecords

public LinkedList<LinkedList<Cstar.Record>> getRecords(DataSet dataSet,
 List<Node> possibleCauses,
 List<Node> possibleEffects,
 int topBracket,
 String path)

Returns records for a set of variables with expected number of false positives bounded by q.

Parameters:

dataSet - The full datasets to search over.

possibleCauses - A set of variables in the datasets over which to search.

possibleEffects - The effect variables.

topBracket - a int

path - A path where interim results are to be stored. If null, interim results will not be stored. If the path is specified, then if the process is stopped and restarted, previously computed interim results will be loaded.

Returns:

a LinkedList object

See Also:

• Cstar.Record

makeGraph

public Graph makeGraph(List<Cstar.Record> records)

Makes a graph of the estimated predictors to the effect.

Parameters:

records - The list of records obtained from a method above.

Returns:

a Graph object

setCpdagAlgorithm

public void setCpdagAlgorithm(Cstar.CpdagAlgorithm cpdagAlgorithm)

The CSTaR algorithm can use any CPDAG algorithm; here you can set it.

Parameters:

cpdagAlgorithm - The CPDAG algorithm.

See Also:

• Cstar.CpdagAlgorithm

setVerbose

public void setVerbose(boolean verbose)

Sets whether verbose output will be printed.

Parameters:

verbose - True, if so.

setSelectionAlpha

public void setSelectionAlpha(double selectionAlpha)

Sets the selection alpha.

Parameters:

selectionAlpha - This alpha.

setSampleStyle

public void setSampleStyle(Cstar.SampleStyle sampleStyle)

Sets the sample style.

Parameters:

sampleStyle - This style.

See Also:

• Cstar.SampleStyle

setNumSubsamples

public void setNumSubsamples(int numSubsamples)

Sets the number of subsamples.

Parameters:

numSubsamples - This number.

getDir

public File getDir()

getDir.

Returns:

a File object

makeTable

public String makeTable(LinkedList<Cstar.Record> records)

Returns a text table from the given records

Parameters:

records - a LinkedList object

Returns:

a String object