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

Example 11 with ContinuousVariable

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

the class TestGeneralizedSem method test7.

@Test
public void test7() {
    RandomUtil.getInstance().setSeed(29999483L);
    List<Node> nodes = new ArrayList<>();
    int numVars = 10;
    for (int i = 0; i < numVars; i++) nodes.add(new ContinuousVariable("X" + (i + 1)));
    Graph graph = GraphUtils.randomGraphRandomForwardEdges(nodes, 0, numVars, 30, 15, 15, false, true);
    GeneralizedSemPm pm = new GeneralizedSemPm(graph);
    GeneralizedSemIm im = new GeneralizedSemIm(pm);
    print(im);
    DataSet data = im.simulateDataRecursive(1000, false);
    GeneralizedSemEstimator estimator = new GeneralizedSemEstimator();
    GeneralizedSemIm estIm = estimator.estimate(pm, data);
    print(estIm);
    print(estimator.getReport());
    double aSquaredStar = estimator.getaSquaredStar();
    assertEquals(0.67, aSquaredStar, 0.01);
}

Example 12 with ContinuousVariable

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

the class TestGeneralizedSem method makeTypicalPm.

private GeneralizedSemPm makeTypicalPm() {
    List<Node> variableNodes = new ArrayList<>();
    ContinuousVariable x1 = new ContinuousVariable("X1");
    ContinuousVariable x2 = new ContinuousVariable("X2");
    ContinuousVariable x3 = new ContinuousVariable("X3");
    ContinuousVariable x4 = new ContinuousVariable("X4");
    ContinuousVariable x5 = new ContinuousVariable("X5");
    variableNodes.add(x1);
    variableNodes.add(x2);
    variableNodes.add(x3);
    variableNodes.add(x4);
    variableNodes.add(x5);
    Graph _graph = new EdgeListGraph(variableNodes);
    SemGraph graph = new SemGraph(_graph);
    graph.addDirectedEdge(x1, x3);
    graph.addDirectedEdge(x2, x3);
    graph.addDirectedEdge(x3, x4);
    graph.addDirectedEdge(x2, x4);
    graph.addDirectedEdge(x4, x5);
    graph.addDirectedEdge(x2, x5);
    return new GeneralizedSemPm(graph);
}

Example 13 with ContinuousVariable

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

the class TestDeltaTetradTest method getBollenSimulationExampleData.

private CovarianceMatrix getBollenSimulationExampleData() {
    double[][] d = new double[][] { { 2.034 }, { 0.113, 1.281 }, { 0.510, 0.093, 1.572 }, { 0.105, 0.857, 0.447, 1.708 }, { 0.998, 0.228, 0.170, 0.345, 1.651 } };
    Node y1 = new ContinuousVariable("y1");
    Node y2 = new ContinuousVariable("y2");
    Node y3 = new ContinuousVariable("y3");
    Node y4 = new ContinuousVariable("y4");
    Node y5 = new ContinuousVariable("y5");
    List<Node> nodes = new ArrayList<>();
    nodes.add(y1);
    nodes.add(y2);
    nodes.add(y3);
    nodes.add(y4);
    nodes.add(y5);
    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, 1000);
}

Example 14 with ContinuousVariable

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

the class Mgm method search.

@Override
public Graph search(DataModel ds, Parameters parameters) {
    // Notify the user that you need at least one continuous and one discrete variable to run MGM
    List<Node> variables = ds.getVariables();
    boolean hasContinuous = false;
    boolean hasDiscrete = false;
    for (Node node : variables) {
        if (node instanceof ContinuousVariable) {
            hasContinuous = true;
        }
        if (node instanceof DiscreteVariable) {
            hasDiscrete = true;
        }
    }
    if (!hasContinuous || !hasDiscrete) {
        throw new IllegalArgumentException("You need at least one continuous and one discrete variable to run MGM.");
    }
    if (parameters.getInt("bootstrapSampleSize") < 1) {
        DataSet _ds = DataUtils.getMixedDataSet(ds);
        double mgmParam1 = parameters.getDouble("mgmParam1");
        double mgmParam2 = parameters.getDouble("mgmParam2");
        double mgmParam3 = parameters.getDouble("mgmParam3");
        double[] lambda = { mgmParam1, mgmParam2, mgmParam3 };
        MGM m = new MGM(_ds, lambda);
        return m.search();
    } else {
        Mgm algorithm = new Mgm();
        DataSet data = (DataSet) ds;
        GeneralBootstrapTest search = new GeneralBootstrapTest(data, algorithm, parameters.getInt("bootstrapSampleSize"));
        BootstrapEdgeEnsemble edgeEnsemble = BootstrapEdgeEnsemble.Highest;
        switch(parameters.getInt("bootstrapEnsemble", 1)) {
            case 0:
                edgeEnsemble = BootstrapEdgeEnsemble.Preserved;
                break;
            case 1:
                edgeEnsemble = BootstrapEdgeEnsemble.Highest;
                break;
            case 2:
                edgeEnsemble = BootstrapEdgeEnsemble.Majority;
        }
        search.setEdgeEnsemble(edgeEnsemble);
        search.setParameters(parameters);
        search.setVerbose(parameters.getBoolean("verbose"));
        return search.search();
    }
}

Example 15 with ContinuousVariable

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

the class IndTestMultinomialLogisticRegression method expandVariable.

private List<Node> expandVariable(DataSet dataSet, Node node) {
    if (node instanceof ContinuousVariable) {
        return Collections.singletonList(node);
    }
    if (node instanceof DiscreteVariable && ((DiscreteVariable) node).getNumCategories() < 3) {
        return Collections.singletonList(node);
    }
    if (!(node instanceof DiscreteVariable)) {
        throw new IllegalArgumentException();
    }
    List<String> varCats = new ArrayList<>(((DiscreteVariable) node).getCategories());
    varCats.remove(0);
    List<Node> variables = new ArrayList<>();
    for (String cat : varCats) {
        Node newVar;
        do {
            String newVarName = node.getName() + "MULTINOM" + "." + cat;
            newVar = new DiscreteVariable(newVarName, 2);
        } while (dataSet.getVariable(newVar.getName()) != null);
        variables.add(newVar);
        dataSet.addVariable(newVar);
        int newVarIndex = dataSet.getColumn(newVar);
        int numCases = dataSet.getNumRows();
        for (int l = 0; l < numCases; l++) {
            Object dataCell = dataSet.getObject(l, dataSet.getColumn(node));
            int dataCellIndex = ((DiscreteVariable) node).getIndex(dataCell.toString());
            if (dataCellIndex == ((DiscreteVariable) node).getIndex(cat))
                dataSet.setInt(l, newVarIndex, 1);
            else
                dataSet.setInt(l, newVarIndex, 0);
        }
    }
    return variables;
}