Examples with FisherZScore edu.cmu.tetrad.algcomparison.score.FisherZScore used on opensource projects

Example 1 with FisherZScore

use of edu.cmu.tetrad.algcomparison.score.FisherZScore in project tetrad by cmu-phil.

the class TestFges 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("numMeasures", numMeasures);
        parameters.set("numLatents", 0);
        parameters.set("avgDegree", avgDegree);
        parameters.set("maxDegree", 20);
        parameters.set("maxIndegree", 20);
        parameters.set("maxOutdegree", 20);
        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);
        RandomGraph graph = new RandomForward();
        LinearFisherModel sim = new LinearFisherModel(graph);
        sim.createData(parameters);
        ScoreWrapper score = new FisherZScore();
        Algorithm alg = new edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges(score);
        parameters.set("alpha", 1e-8);
        for (int i = 0; i < 5; i++) {
            Graph out1 = alg.search(sim.getDataModel(0), parameters);
            System.out.println(out1);
        }
    } else {
        new TestFges().test9();
    }
}

Example 2 with FisherZScore

use of edu.cmu.tetrad.algcomparison.score.FisherZScore 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);
    }
}