Search in sources :

Example 16 with Simulations

use of edu.cmu.tetrad.algcomparison.simulation.Simulations in project tetrad by cmu-phil.

the class ExampleStARS method main.

public static void main(String... args) {
    Parameters parameters = new Parameters();
    // parameters.set("numMeasures", 100);
    // parameters.set("avgDegree", 2, 4);
    // parameters.set("sampleSize", 100, 500);
    // parameters.set("numRuns", 5);
    parameters.set("numMeasures", 200);
    parameters.set("avgDegree", 2, 4, 6);
    parameters.set("sampleSize", 100, 500);
    parameters.set("numRuns", 2);
    parameters.set("differentGraphs", true);
    parameters.set("numLatents", 0);
    parameters.set("maxDegree", 100);
    parameters.set("maxIndegree", 100);
    parameters.set("maxOutdegree", 100);
    parameters.set("connected", false);
    parameters.set("coefLow", 0.2);
    parameters.set("coefHigh", 0.9);
    parameters.set("varLow", 1);
    parameters.set("varHigh", 3);
    parameters.set("verbose", false);
    parameters.set("coefSymmetric", true);
    parameters.set("percentDiscrete", 0);
    parameters.set("numCategories", 3);
    parameters.set("differentGraphs", true);
    parameters.set("intervalBetweenShocks", 10);
    parameters.set("intervalBetweenRecordings", 10);
    parameters.set("fisherEpsilon", 0.001);
    parameters.set("randomizeColumns", true);
    parameters.set("alpha", 0.01);
    parameters.set("depth", -1);
    parameters.set("penaltyDiscount", 2);
    parameters.set("useMaxPOrientationHeuristic", false);
    parameters.set("maxPOrientationMaxPathLength", 3);
    parameters.set("verbose", false);
    parameters.set("scaleFreeAlpha", 0.00001);
    parameters.set("scaleFreeBeta", 0.4);
    parameters.set("scaleFreeDeltaIn", .1);
    parameters.set("scaleFreeDeltaOut", 3);
    parameters.set("symmetricFirstStep", false);
    parameters.set("faithfulnessAssumed", true);
    parameters.set("maxDegree", 100);
    parameters.set("StARS.tolerance", .5);
    parameters.set("StARS.cutoff", .05);
    parameters.set("numSubsamples", 7);
    parameters.set("percentSubsampleSize", .5);
    parameters.set("percentStability", .5);
    Statistics statistics = new Statistics();
    statistics.add(new ParameterColumn("numMeasures"));
    statistics.add(new ParameterColumn("avgDegree"));
    statistics.add(new ParameterColumn("sampleSize"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    statistics.add(new ArrowheadPrecision());
    statistics.add(new ArrowheadRecall());
    statistics.add(new ElapsedTime());
    statistics.setWeight("AP", 0.25);
    statistics.setWeight("AR", 0.25);
    statistics.setWeight("AHP", 0.25);
    statistics.setWeight("AHR", 0.25);
    Algorithms algorithms = new Algorithms();
    parameters.set("logScale", false);
    algorithms.add(new StabilitySelection(new Fges(new SemBicScore())));
    algorithms.add(new StARS(new Fges(new SemBicScore()), "penaltyDiscount", 1, 5));
    algorithms.add(new FirstInflection(new Fges(new SemBicScore()), "penaltyDiscount", 1, 5, .1));
    // parameters.set("penaltyDiscount", 5, 11, 15);
    // algorithms.add(new Fges(new SemBicScore()));
    // parameters.set("logScale", true);
    // Algorithm fges = new Fges(new FisherZScore());
    // algorithms.add(new StARS(fges, "alpha", -10, -2, -8));
    // algorithms.add(new FirstInflection(fges, "alpha", -10, -2, -3));
    Simulations simulations = new Simulations();
    simulations.add(new LinearFisherModel(new RandomForward()));
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(true);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(true);
    comparison.setComparisonGraph(Comparison.ComparisonGraph.Pattern_of_the_true_DAG);
    comparison.compareFromSimulations("first.inflection", simulations, algorithms, statistics, parameters);
}
Also used : Simulations(edu.cmu.tetrad.algcomparison.simulation.Simulations) Parameters(edu.cmu.tetrad.util.Parameters) LinearFisherModel(edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel) StabilitySelection(edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection) StARS(edu.cmu.tetrad.algcomparison.algorithm.StARS) RandomForward(edu.cmu.tetrad.algcomparison.graph.RandomForward) Fges(edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges) Algorithms(edu.cmu.tetrad.algcomparison.algorithm.Algorithms) Comparison(edu.cmu.tetrad.algcomparison.Comparison) SemBicScore(edu.cmu.tetrad.algcomparison.score.SemBicScore) FirstInflection(edu.cmu.tetrad.algcomparison.algorithm.FirstInflection)

Example 17 with Simulations

use of edu.cmu.tetrad.algcomparison.simulation.Simulations in project tetrad by cmu-phil.

the class ExampleCompareSimulation method main.

public static void main(String... args) {
    if (args.length > 0) {
        int numMeasures = Integer.parseInt(args[0]);
        int avgDegree = Integer.parseInt(args[1]);
        Parameters parameters = new Parameters();
        // parameters.set("minCategories", 3);
        // parameters.set("maxCategories", 3);
        parameters.set("numRuns", 2);
        parameters.set("differentGraphs", true);
        parameters.set("sampleSize", 1000);
        parameters.set("numMeasures", numMeasures);
        parameters.set("numLatents", 0);
        parameters.set("avgDegree", avgDegree);
        parameters.set("maxDegree", 100);
        parameters.set("maxIndegree", 100);
        parameters.set("maxOutdegree", 100);
        parameters.set("connected", false);
        parameters.set("coefLow", 0.2);
        parameters.set("coefHigh", 0.9);
        parameters.set("varLow", 1);
        parameters.set("varHigh", 3);
        parameters.set("verbose", false);
        parameters.set("coefSymmetric", true);
        parameters.set("numRuns", 1);
        parameters.set("percentDiscrete", 0);
        parameters.set("numCategories", 3);
        parameters.set("differentGraphs", true);
        parameters.set("sampleSize", 1000);
        parameters.set("intervalBetweenShocks", 10);
        parameters.set("intervalBetweenRecordings", 10);
        parameters.set("fisherEpsilon", 0.001);
        parameters.set("randomizeColumns", true);
        parameters.set("alpha", 1e-8);
        parameters.set("depth", -1);
        parameters.set("penaltyDiscount", 4);
        parameters.set("useMaxPOrientationHeuristic", false);
        parameters.set("maxPOrientationMaxPathLength", 3);
        parameters.set("verbose", false);
        parameters.set("scaleFreeAlpha", 0.00001);
        parameters.set("scaleFreeBeta", 0.4);
        parameters.set("scaleFreeDeltaIn", .1);
        parameters.set("scaleFreeDeltaOut", 3);
        parameters.set("symmetricFirstStep", false);
        parameters.set("faithfulnessAssumed", true);
        parameters.set("maxDegree", 100);
        Statistics statistics = new Statistics();
        statistics.add(new ParameterColumn("numMeasures"));
        statistics.add(new ParameterColumn("avgDegree"));
        statistics.add(new AdjacencyPrecision());
        statistics.add(new AdjacencyRecall());
        statistics.add(new ArrowheadPrecision());
        statistics.add(new ArrowheadRecall());
        // statistics.add(new NumBidirectedEdges());
        // statistics.add(new MathewsCorrAdj());
        // statistics.add(new MathewsCorrArrow());
        // statistics.add(new F1Adj());
        // statistics.add(new F1Arrow());
        // statistics.add(new SHD());
        statistics.add(new ElapsedTime());
        statistics.setWeight("AP", 0.25);
        statistics.setWeight("AR", 0.25);
        statistics.setWeight("AHP", 0.25);
        statistics.setWeight("AHR", 0.25);
        Algorithms algorithms = new Algorithms();
        // algorithms.add(new Pc(new FisherZ()));
        // algorithms.add(new Pc(new SemBicTest()));
        // algorithms.add(new Cpc(new FisherZ()));
        // algorithms.add(new PcStable(new FisherZ()));
        // algorithms.add(new CpcStable(new FisherZ()));
        // algorithms.add(new PcStableMax(new FisherZ(), false));
        // algorithms.add(new PcStableMax(new SemBicTest(), false));
        algorithms.add(new Fges(new FisherZScore(), false));
        // algorithms.add(new Fges(new SemBicScore(), false));
        Simulations simulations = new Simulations();
        simulations.add(new LinearFisherModel(new RandomForward()));
        Comparison comparison = new Comparison();
        comparison.setShowAlgorithmIndices(true);
        comparison.setShowSimulationIndices(true);
        comparison.setSortByUtility(false);
        comparison.setShowUtilities(true);
        comparison.compareFromSimulations("comparisonJoe", simulations, algorithms, statistics, parameters);
    }
}
Also used : FisherZScore(edu.cmu.tetrad.algcomparison.score.FisherZScore) Simulations(edu.cmu.tetrad.algcomparison.simulation.Simulations) Parameters(edu.cmu.tetrad.util.Parameters) LinearFisherModel(edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel) RandomForward(edu.cmu.tetrad.algcomparison.graph.RandomForward) Algorithms(edu.cmu.tetrad.algcomparison.algorithm.Algorithms) Comparison(edu.cmu.tetrad.algcomparison.Comparison)

Example 18 with Simulations

use of edu.cmu.tetrad.algcomparison.simulation.Simulations in project tetrad by cmu-phil.

the class TestImagesSimulation method test1.

public void test1() {
    Parameters parameters = new Parameters();
    parameters.set("numRuns", 1);
    parameters.set("numMeasures", 100);
    parameters.set("avgDegree", 8);
    // parameters.set("maxDegree", 8);
    // parameters.set("maxIndegree",  3);
    // parameters.set("maxOutdegree", 3);
    parameters.set("sampleSize", 500);
    parameters.set("penaltyDiscount", 4);
    // parameters.set("alpha", 0.001);
    // parameters.set("maxDegree", 5);
    // parameters.set("numCategoriesToDiscretize", 3);
    parameters.set("intervalBetweenRecordings", 20);
    parameters.set("varLow", 1.);
    parameters.set("varHigh", 3.);
    parameters.set("coefLow", .1);
    parameters.set("coefHigh", 1);
    parameters.set("coefSymmetric", true);
    parameters.set("meanLow", -1);
    parameters.set("meanHigh", 1);
    // parameters.set("scaleFreeAlpha", .9);
    // parameters.set("scaleFreeBeta", .05);
    // parameters.set("scaleFreeDeltaIn", 3);
    // parameters.set("scaleFreeDeltaOut", .1);
    parameters.set("numRuns", 1);
    parameters.set("randomSelectionSize", 3);
    Statistics statistics = new Statistics();
    // statistics.add(new ParameterColumn("numCategories"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    statistics.add(new ArrowheadPrecision());
    statistics.add(new ArrowheadRecall());
    statistics.add(new ElapsedTime());
    statistics.setWeight("AP", 1.0);
    statistics.setWeight("AR", 0.5);
    Algorithms algorithms = new Algorithms();
    algorithms.add(new ImagesSemBic());
    algorithms.add(new ImagesPcStableMax());
    Simulations simulations = new Simulations();
    simulations.add(new LinearFisherModel(new RandomForward()));
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(false);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(true);
    // comparison.setSaveGraphs(true);
    comparison.setTabDelimitedTables(false);
    comparison.compareFromSimulations("comparison", simulations, algorithms, statistics, parameters);
}
Also used : Simulations(edu.cmu.tetrad.algcomparison.simulation.Simulations) Parameters(edu.cmu.tetrad.util.Parameters) LinearFisherModel(edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel) ImagesPcStableMax(edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesPcStableMax) RandomForward(edu.cmu.tetrad.algcomparison.graph.RandomForward) Algorithms(edu.cmu.tetrad.algcomparison.algorithm.Algorithms) ImagesSemBic(edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesSemBic) Comparison(edu.cmu.tetrad.algcomparison.Comparison)

Example 19 with Simulations

use of edu.cmu.tetrad.algcomparison.simulation.Simulations in project tetrad by cmu-phil.

the class TestSimulatedFmri2 method TestCycles_Data_fMRI_FASK.

public void TestCycles_Data_fMRI_FASK() {
    Parameters parameters = new Parameters();
    parameters.set("penaltyDiscount", 8);
    parameters.set("depth", -1);
    parameters.set("faskDelta", -0.2);
    parameters.set("twoCycleAlpha", 1e-15);
    parameters.set("numRuns", 60);
    // parameters.set("randomSelectionSize", 1);
    parameters.set("Structure", "Placeholder");
    Statistics statistics = new Statistics();
    statistics.add(new ParameterColumn("Structure"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    // statistics.add(new MathewsCorrAdj());
    statistics.add(new ArrowheadPrecision());
    statistics.add(new ArrowheadRecall());
    statistics.add(new TwoCyclePrecision());
    statistics.add(new TwoCycleRecall());
    statistics.add(new TwoCycleFalsePositive());
    statistics.add(new TwoCycleFalseNegative());
    statistics.add(new TwoCycleTruePositive());
    statistics.add(new ElapsedTime());
    statistics.setWeight("AHR", 1.0);
    statistics.setWeight("2CP", 1.0);
    statistics.setWeight("2CR", 1.0);
    statistics.setWeight("2CFP", 1.0);
    Simulations simulations = new Simulations();
    String dir = "/Users/user/Downloads/CyclesTestingData/";
    String subdir = "data_fslfilter_concat";
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network1_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network2_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network3_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network4_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont_p3n7", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont_p7n3", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network6_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network6_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network7_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network7_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_amp_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_amp_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_cont_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_amp_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_amp_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_cont_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Diamond", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Markov_Complex_1", subdir));
    Algorithms algorithms = new Algorithms();
    algorithms.add(new edu.cmu.tetrad.algcomparison.algorithm.multi.Fask(new SemBicScore()));
    // 
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(true);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(false);
    comparison.setSaveGraphs(false);
    comparison.setTabDelimitedTables(false);
    comparison.setSaveGraphs(true);
    String directory = "comparison_testing_nonconcat";
    comparison.compareFromSimulations(directory, simulations, algorithms, statistics, parameters);
}
Also used : Simulations(edu.cmu.tetrad.algcomparison.simulation.Simulations) Parameters(edu.cmu.tetrad.util.Parameters) Algorithms(edu.cmu.tetrad.algcomparison.algorithm.Algorithms) Comparison(edu.cmu.tetrad.algcomparison.Comparison) SemBicScore(edu.cmu.tetrad.algcomparison.score.SemBicScore)

Example 20 with Simulations

use of edu.cmu.tetrad.algcomparison.simulation.Simulations in project tetrad by cmu-phil.

the class TestSimulatedFmri method task.

private void task(boolean testing) {
    Parameters parameters = new Parameters();
    parameters.set("penaltyDiscount", 4);
    parameters.set("depth", -1);
    parameters.set("twoCycleAlpha", 1e-10);
    parameters.set("faskDelta", -.2);
    parameters.set("reverseOrientationsBySignOfCorrelation", false);
    parameters.set("reverseOrientationsBySkewnessOfVariables", false);
    parameters.set("numRuns", 10);
    parameters.set("randomSelectionSize", 10);
    parameters.set("Structure", "Placeholder");
    Statistics statistics = new Statistics();
    statistics.add(new ParameterColumn("Structure"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    // statistics.add(new MathewsCorrAdj());
    statistics.add(new ArrowheadPrecision());
    statistics.add(new ArrowheadRecall());
    statistics.add(new TwoCyclePrecision());
    statistics.add(new TwoCycleRecall());
    statistics.add(new TwoCycleFalsePositive());
    statistics.add(new TwoCycleFalseNegative());
    statistics.add(new TwoCycleTruePositive());
    statistics.add(new ElapsedTime());
    statistics.setWeight("AHR", 1.0);
    statistics.setWeight("2CP", 1.0);
    statistics.setWeight("2CR", 1.0);
    statistics.setWeight("2CFP", 1.0);
    Simulations simulations = new Simulations();
    if (!testing) {
        String dir = "/Users/user/Downloads/Cycles_Data_fMRI/";
        String subdir = "data_fslfilter";
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network1_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network2_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network3_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network4_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_contr", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_contr_p2n6", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_contr_p6n2", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network6_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network6_contr", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network7_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network7_contr", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_amp_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_amp_contr", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_contr_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_amp_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_amp_contr", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_contr_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Diamond", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Markov_Complex_1", subdir));
    } else {
        String dir = "/Users/user/Downloads/CyclesTestingData/";
        String subdir = "data_fslfilter";
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network1_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network2_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network3_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network4_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont_p3n7", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont_p7n3", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network6_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network6_cont", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network7_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network7_cont", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_amp_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_amp_cont", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_cont_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_amp_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_amp_cont", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_cont_amp", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Diamond", subdir));
        simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Markov_Complex_1", subdir));
    }
    Algorithms algorithms = new Algorithms();
    algorithms.add(new FaskConcatenated(new SemBicScore()));
    // algorithms.add(new FaskGfciConcatenated(new SemBicTest()));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.RSkew));
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(true);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(false);
    comparison.setSaveGraphs(false);
    comparison.setTabDelimitedTables(false);
    comparison.setSaveGraphs(true);
    String directory;
    if (!testing) {
        directory = "comparison_training";
    } else {
        directory = "comparison_testing";
    }
    comparison.compareFromSimulations(directory, simulations, algorithms, statistics, parameters);
}
Also used : Simulations(edu.cmu.tetrad.algcomparison.simulation.Simulations) Parameters(edu.cmu.tetrad.util.Parameters) Algorithms(edu.cmu.tetrad.algcomparison.algorithm.Algorithms) Comparison(edu.cmu.tetrad.algcomparison.Comparison) SemBicScore(edu.cmu.tetrad.algcomparison.score.SemBicScore)

Aggregations

Simulations (edu.cmu.tetrad.algcomparison.simulation.Simulations)22 Algorithms (edu.cmu.tetrad.algcomparison.algorithm.Algorithms)17 Parameters (edu.cmu.tetrad.util.Parameters)17 Comparison (edu.cmu.tetrad.algcomparison.Comparison)16 RandomForward (edu.cmu.tetrad.algcomparison.graph.RandomForward)10 SemBicScore (edu.cmu.tetrad.algcomparison.score.SemBicScore)9 Algorithm (edu.cmu.tetrad.algcomparison.algorithm.Algorithm)5 ExternalAlgorithm (edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm)4 MultiDataSetAlgorithm (edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm)4 Fges (edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges)4 LinearFisherModel (edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel)4 LoadDataAndGraphs (edu.cmu.tetrad.algcomparison.simulation.LoadDataAndGraphs)4 FisherZ (edu.cmu.tetrad.algcomparison.independence.FisherZ)3 SemSimulation (edu.cmu.tetrad.algcomparison.simulation.SemSimulation)3 FirstInflection (edu.cmu.tetrad.algcomparison.algorithm.FirstInflection)2 File (java.io.File)2 StARS (edu.cmu.tetrad.algcomparison.algorithm.StARS)1 StabilitySelection (edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection)1 Fask (edu.cmu.tetrad.algcomparison.algorithm.multi.Fask)1 ImagesPcStableMax (edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesPcStableMax)1