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

Example 26 with ICovarianceMatrix

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

the class TestSem method constructCovMatrix2.

private ICovarianceMatrix constructCovMatrix2() {
    String[] vars = new String[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8" };
    int sampleSize = 173;
    double[][] arr = { { 1.0 }, { .215, 1.0 }, { -.164, -.472, 1.0 }, { .112, .079, -.157, 1.0 }, { .034, .121, -.184, .407, 1.0 }, { .101, .197, -.190, .176, .120, 1.0 }, { .071, -.172, .206, -.049, -.084, -.291, 1.0 }, { .043, -.038, -.037, -.062, .028, .166, -.149, 1.0 } };
    double[][] m = MatrixUtils.convertLowerTriangleToSymmetric(arr);
    TetradMatrix m2 = new TetradMatrix(m);
    return new CovarianceMatrix(DataUtils.createContinuousVariables(vars), m2, sampleSize);
}

Example 27 with ICovarianceMatrix

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

the class TestSem method testSet1.

@Test
public void testSet1() {
    Graph graph = constructGraph1();
    SemPm semPm = new SemPm(graph);
    ICovarianceMatrix covMatrix = constructCovMatrix1();
    new SemIm(semPm, covMatrix);
}

Example 28 with ICovarianceMatrix

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

the class TestSem method constructCovMatrix1.

private ICovarianceMatrix constructCovMatrix1() {
    String[] vars = new String[] { "X1", "X2", "X3", "X4", "X5" };
    double[][] arr = { { 1.04408 }, { 0.80915, 1.55607 }, { 0.89296, 1.67375, 2.87584 }, { 2.23792, 2.68536, 3.94996, 7.78259 }, { 1.17516, 1.36337, 1.99039, 4.04533, 3.14922 } };
    double[][] m = MatrixUtils.convertLowerTriangleToSymmetric(arr);
    TetradMatrix m2 = new TetradMatrix(m);
    return new CovarianceMatrix(DataUtils.createContinuousVariables(vars), m2, 1000);
}

Example 29 with ICovarianceMatrix

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

the class TestSemIm method test3.

@Test
public void test3() {
    Graph graph = constructGraph1();
    SemPm semPm = new SemPm(graph);
    SemIm semIm = new SemIm(semPm);
    DataSet dataSetContColumnContinuous = semIm.simulateData(500, false);
    ICovarianceMatrix covMatrix = new CovarianceMatrix(dataSetContColumnContinuous);
    SemEstimator estimator2 = new SemEstimator(covMatrix, semPm);
    estimator2.estimate();
    estimator2.getEstimatedSem();
    SemEstimator estimator3 = new SemEstimator(covMatrix, semPm);
    estimator3.estimate();
    estimator3.getEstimatedSem();
    SemPm semPm4 = new SemPm(graph);
    SemEstimator estimator4 = new SemEstimator(covMatrix, semPm4);
    estimator4.estimate();
    estimator4.getEstimatedSem();
    SemPm semPm5 = new SemPm(graph);
    SemEstimator estimator5 = new SemEstimator(covMatrix, semPm5);
    estimator5.estimate();
    estimator5.getEstimatedSem();
}

Example 30 with ICovarianceMatrix

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

the class IndTestTrekSep method indTestSubset.

// ==========================PUBLIC METHODS=============================//
/**
 * Creates a new independence test instance for a subset of the variables.
 */
public IndependenceTest indTestSubset(List<Node> vars) {
    if (vars.isEmpty()) {
        throw new IllegalArgumentException("Subset may not be empty.");
    }
    for (Node var : vars) {
        if (!variables.contains(var)) {
            throw new IllegalArgumentException("All vars must be original vars");
        }
    }
    int[] indices = new int[vars.size()];
    for (int i = 0; i < indices.length; i++) {
        indices[i] = indexMap.get(vars.get(i));
    }
    ICovarianceMatrix newCovMatrix = covMatrix.getSubmatrix(indices);
    double alphaNew = getAlpha();
    return new IndTestTrekSep(newCovMatrix, alphaNew, clustering, latents);
}