Examples with SemEstimator edu.cmu.tetrad.sem.SemEstimator used on opensource projects

Example 16 with SemEstimator

use of edu.cmu.tetrad.sem.SemEstimator in project tetrad by cmu-phil.

the class SemEstimatorWrapper method setParams.

private boolean setParams(SemPmWrapper semPmWrapper, DataModelList dataModel) {
    for (DataModel model : dataModel) {
        if (model instanceof DataSet) {
            DataSet dataSet = (DataSet) model;
            SemPm semPm = semPmWrapper.getSemPm();
            this.semPm = semPm;
            SemEstimator estimator = new SemEstimator(dataSet, semPm, getOptimizer());
            estimator.setNumRestarts(getParams().getInt("numRestarts", 1));
            estimator.setScoreType((ScoreType) getParams().get("scoreType", ScoreType.Fgls));
            if (!degreesOfFreedomCheck(semPm)) {
                return true;
            }
            estimator.estimate();
            getMultipleResultList().add(estimator);
        } else if (model instanceof ICovarianceMatrix) {
            ICovarianceMatrix covMatrix = new CovarianceMatrix((ICovarianceMatrix) model);
            SemPm semPm = semPmWrapper.getSemPm();
            this.semPm = semPm;
            SemEstimator estimator = new SemEstimator(covMatrix, semPm, getOptimizer());
            estimator.setNumRestarts(getParams().getInt("numRestarts", 1));
            estimator.setScoreType((ScoreType) getParams().get("scoreType", ScoreType.Fgls));
            if (!degreesOfFreedomCheck(semPm)) {
                return true;
            }
            estimator.estimate();
            getMultipleResultList().add(estimator);
        } else {
            throw new IllegalArgumentException("Data must consist of continuous data sets or covariance matrices.");
        }
    }
    return false;
}

Example 17 with SemEstimator

use of edu.cmu.tetrad.sem.SemEstimator in project tetrad by cmu-phil.

the class TestStandardizedSem method test1.

// Test the code that standardizes a data set.
@Test
public void test1() {
    List<Node> nodes = new ArrayList<>();
    for (int i = 0; i < 5; i++) {
        nodes.add(new ContinuousVariable("X" + (i + 1)));
    }
    SemGraph graph = new SemGraph(new Dag(GraphUtils.randomGraph(nodes, 0, 5, 30, 15, 15, false)));
    SemPm pm = new SemPm(graph);
    SemIm im = new SemIm(pm);
    DataSet dataSet = im.simulateData(1000, false);
    TetradMatrix _dataSet = dataSet.getDoubleData();
    _dataSet = DataUtils.standardizeData(_dataSet);
    DataSet dataSetStandardized = ColtDataSet.makeData(dataSet.getVariables(), _dataSet);
    DataUtils.cov(_dataSet);
    DataUtils.mean(_dataSet);
    SemEstimator estimator = new SemEstimator(dataSetStandardized, pm);
    SemIm imStandardized = estimator.estimate();
    imStandardized.getEdgeCoef();
    imStandardized.getErrCovar();
    new TetradVector(imStandardized.getMeans());
    imStandardized.getEdgeCoef();
    imStandardized.getErrCovar();
    StandardizedSemIm sem = new StandardizedSemIm(im);
    imStandardized.getEdgeCoef();
    imStandardized.getErrCovar();
    assertTrue(isStandardized(sem));
}

Example 18 with SemEstimator

use of edu.cmu.tetrad.sem.SemEstimator in project tetrad by cmu-phil.

the class GraphWithParameters method regress.

/**
 * creates a PatternWithParameters by running a regression, given a graph and data
 */
public static GraphWithParameters regress(DataSet dataSet, Graph graph) {
    SemPm semPmEstDag = new SemPm(graph);
    SemEstimator estimatorEstDag = new SemEstimator(dataSet, semPmEstDag);
    estimatorEstDag.estimate();
    SemIm semImEstDag = estimatorEstDag.getEstimatedSem();
    GraphWithParameters estimatedGraph = new GraphWithParameters(semImEstDag, graph);
    return estimatedGraph;
}