Examples with CovarianceMatrix edu.cmu.tetrad.data.CovarianceMatrix used on opensource projects

Example 11 with CovarianceMatrix

use of edu.cmu.tetrad.data.CovarianceMatrix in project tetrad by cmu-phil.

the class CovMatrixAverageWrapper method calcAverage.

private void calcAverage(List<DataWrapper> wrappers) {
    List<TetradMatrix> cov = new ArrayList<>();
    for (int i = 0; i < wrappers.size(); i++) {
        DataModel selectedDataModel = wrappers.get(i).getSelectedDataModel();
        if (!(selectedDataModel instanceof ICovarianceMatrix)) {
            throw new IllegalArgumentException("Sorry, this is an average only over covariance matrices.");
        }
        cov.add(((ICovarianceMatrix) selectedDataModel).getMatrix());
    }
    TetradMatrix cov3 = new TetradMatrix(cov.get(0).rows(), cov.get(0).rows());
    for (int i = 0; i < cov.get(0).rows(); i++) {
        for (int j = 0; j < cov.get(0).rows(); j++) {
            double c = 0.0;
            for (int k = 0; k < cov.size(); k++) {
                c += cov.get(k).get(i, j);
            }
            c /= cov.size();
            cov3.set(i, j, c);
            cov3.set(j, i, c);
        }
    }
    DataModel m = wrappers.get(0).getSelectedDataModel();
    ICovarianceMatrix _cov = (ICovarianceMatrix) m;
    List<Node> nodes = _cov.getVariables();
    int n = _cov.getSampleSize();
    ICovarianceMatrix covWrapper = new CovarianceMatrix(nodes, cov3, n);
    setDataModel(covWrapper);
}

Example 12 with CovarianceMatrix

use of edu.cmu.tetrad.data.CovarianceMatrix in project tetrad by cmu-phil.

the class TestDeltaTetradTest method test3.

@Test
public void test3() {
    SemPm pm = makePm();
    DataSet data = new SemIm(pm).simulateData(1000, false);
    CovarianceMatrix cov = new CovarianceMatrix(data);
    List<Node> variables = data.getVariables();
    Node x1 = variables.get(0);
    Node x2 = variables.get(1);
    Node x3 = variables.get(2);
    Node x4 = variables.get(3);
    Node x5 = variables.get(4);
    Tetrad t1234 = new Tetrad(x1, x2, x3, x4);
    Tetrad t1342 = new Tetrad(x1, x3, x4, x2);
    Tetrad t1423 = new Tetrad(x1, x4, x2, x3);
    DeltaTetradTest test1 = new DeltaTetradTest(data);
    // DeltaTetradTest test = new DeltaTetradTest(new CorrelationMatrix(cov));
    double chiSq1 = test1.calcChiSquare(t1234, t1342);
    DeltaTetradTest test2 = new DeltaTetradTest(cov);
    // DeltaTetradTest test = new DeltaTetradTest(new CorrelationMatrix(cov));
    double chiSq2 = test2.calcChiSquare(t1234, t1342);
}

Example 13 with CovarianceMatrix

use of edu.cmu.tetrad.data.CovarianceMatrix in project tetrad by cmu-phil.

the class TestDeltaTetradTest method getBollenExample2Data.

private CovarianceMatrix getBollenExample2Data() {
    // Union sentiment.
    double[][] d = new double[][] { { 14.610 }, { -5.250, 11.017 }, { -8.057, 11.087, 31.971 }, { -0.482, 0.677, 1.559, 1.021 }, { -18.857, 17.861, 28.250, 7.139, 215.662 } };
    Node y1 = new ContinuousVariable("y1");
    Node y2 = new ContinuousVariable("y2");
    Node y3 = new ContinuousVariable("y3");
    Node x1 = new ContinuousVariable("x1");
    Node x2 = new ContinuousVariable("x2");
    List<Node> nodes = new ArrayList<>();
    nodes.add(y1);
    nodes.add(y2);
    nodes.add(y3);
    nodes.add(x1);
    nodes.add(x2);
    TetradMatrix matrix = new TetradMatrix(5, 5);
    for (int i = 0; i < 5; i++) {
        for (int j = 0; j <= i; j++) {
            matrix.set(i, j, d[i][j]);
            matrix.set(j, i, d[i][j]);
        }
    }
    return new CovarianceMatrix(nodes, matrix, 173);
}

Example 14 with CovarianceMatrix

use of edu.cmu.tetrad.data.CovarianceMatrix in project tetrad by cmu-phil.

the class TestDeltaTetradTest method getBollenExample1Data.

private CovarianceMatrix getBollenExample1Data() {
    // Sympathy and anger, p. 164.
    double[][] d = new double[][] { { 6.982 }, { 4.686, 6.047 }, { 4.335, 3.307, 5.037 }, { -2.294, -1.453, -1.979, 5.569 }, { -2.209, -1.262, -1.738, 3.931, 5.328 }, { -1.671, -1.401, -1.564, 3.915, 3.601, 4.977 } };
    Node v1 = new ContinuousVariable("v1");
    Node v2 = new ContinuousVariable("v2");
    Node v3 = new ContinuousVariable("v3");
    Node v4 = new ContinuousVariable("v4");
    Node v5 = new ContinuousVariable("v5");
    Node v6 = new ContinuousVariable("v6");
    List<Node> nodes = new ArrayList<>();
    nodes.add(v1);
    nodes.add(v2);
    nodes.add(v3);
    nodes.add(v4);
    nodes.add(v5);
    nodes.add(v6);
    TetradMatrix matrix = new TetradMatrix(6, 6);
    for (int i = 0; i < 6; i++) {
        for (int j = 0; j <= i; j++) {
            matrix.set(i, j, d[i][j]);
            matrix.set(j, i, d[i][j]);
        }
    }
    return new CovarianceMatrix(nodes, matrix, 138);
}

Example 15 with CovarianceMatrix

use of edu.cmu.tetrad.data.CovarianceMatrix in project tetrad by cmu-phil.

the class TestDeltaTetradTest method testBollenSimulationExample.

// Bollen 2000 A Tetrad Test for Causal Indicators, p. 13.
@Test
public void testBollenSimulationExample() {
    CovarianceMatrix cov = getBollenSimulationExampleData();
    List<Node> variables = cov.getVariables();
    Node y1 = variables.get(0);
    Node y2 = variables.get(1);
    Node y3 = variables.get(2);
    Node y4 = variables.get(3);
    Node y5 = variables.get(4);
    Tetrad t1 = new Tetrad(y1, y2, y3, y4);
    Tetrad t2 = new Tetrad(y1, y2, y4, y3);
    Tetrad t3 = new Tetrad(y1, y3, y4, y2);
    Tetrad t4 = new Tetrad(y1, y2, y3, y5);
    Tetrad t5 = new Tetrad(y1, y2, y5, y3);
    Tetrad t6 = new Tetrad(y1, y3, y5, y2);
    Tetrad t7 = new Tetrad(y1, y2, y4, y5);
    Tetrad t8 = new Tetrad(y1, y2, y5, y4);
    Tetrad t9 = new Tetrad(y1, y4, y5, y2);
    Tetrad t10 = new Tetrad(y1, y3, y4, y5);
    Tetrad t11 = new Tetrad(y1, y3, y5, y4);
    Tetrad t12 = new Tetrad(y1, y4, y5, y3);
    Tetrad t13 = new Tetrad(y2, y3, y4, y5);
    Tetrad t14 = new Tetrad(y2, y3, y5, y4);
    Tetrad t15 = new Tetrad(y2, y4, y5, y3);
    Tetrad[] tetrads = new Tetrad[] { t1, t2, t3, t4 };
    DeltaTetradTest test = new DeltaTetradTest(cov);
    double chiSq = test.calcChiSquare(tetrads[0]);
    double pValue = test.getPValue();
    assertEquals(58.1, chiSq, 0.1);
    assertEquals(2.46E-14, pValue, .1E-14);
    Tetrad[] independentTetrads = new Tetrad[] { t1, t2, t4, t6, t10 };
    chiSq = test.calcChiSquare(independentTetrads[0]);
    pValue = test.getPValue();
    assertEquals(58.1, chiSq, 0.1);
    assertEquals(2.46E-14, pValue, 0.1E-14);
    {
        chiSq = test.calcChiSquare(independentTetrads);
        pValue = test.getPValue();
        assertEquals(89.34, chiSq, 0.01);
        assertEquals(0.0, pValue, 0.01);
    }
// They get chsq = 64.13 and so do I.
}