Examples of org.apache.commons.math.distribution.TDistributionImpl

Package org.apache.commons.math.distribution

Examples of org.apache.commons.math.distribution.TDistributionImpl

org.apache.commons.math.distribution.TDistributionImpl
Default implementation of {@link org.apache.commons.math.distribution.TDistribution}. @version $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $

    /**
     * Verify that direct t-tests using standard error estimates are consistent
     * with reported p-values
     */
    public void testStdErrorConsistency() throws Exception {
        TDistribution tDistribution = new TDistributionImpl(45);
        RealMatrix matrix = createRealMatrix(swissData, 47, 5);
        PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
        RealMatrix rValues = corrInstance.getCorrelationMatrix();
        RealMatrix pValues = corrInstance.getCorrelationPValues();
        RealMatrix stdErrors = corrInstance.getCorrelationStandardErrors();
        for (int i = 0; i < 5; i++) {
            for (int j = 0; j < i; j++) {
                double t = FastMath.abs(rValues.getEntry(i, j)) / stdErrors.getEntry(i, j);
                double p = 2 * (1 - tDistribution.cumulativeProbability(t));
                assertEquals(p, pValues.getEntry(i, j), 10E-15);
            }
        }
    }

View Full Code Here

        }
        TestUtils.assertChiSquareAccept(expected, counts, 0.001);
    }
    
    public void testNextT() throws Exception {
        double[] quartiles = TestUtils.getDistributionQuartiles(new TDistributionImpl(10));
        long[] counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextT(10);
            TestUtils.updateCounts(value, counts, quartiles);

View Full Code Here

     * 
     * @return matrix of p-values
     * @throws MathException if an error occurs estimating probabilities
     */
    public RealMatrix getCorrelationPValues() throws MathException {
        TDistribution tDistribution = new TDistributionImpl(nObs - 2);
        int nVars = correlationMatrix.getColumnDimension();
        double[][] out = new double[nVars][nVars];
        for (int i = 0; i < nVars; i++) {
            for (int j = 0; j < nVars; j++) {
                if (i == j) {
                    out[i][j] = 0d;
                } else {
                    double r = correlationMatrix.getEntry(i, j);
                    double t = Math.abs(r * Math.sqrt((nObs - 2)/(1 - r * r)));
                    out[i][j] = 2 * (1 - tDistribution.cumulativeProbability(t));
                }
            }
        }
        return new BlockRealMatrix(out);
    }

View Full Code Here

    
    /**
     * Default constructor.
     */
    public TTestImpl() {
        this(new TDistributionImpl(1.0));
    }

View Full Code Here

    /**
     * Verify that direct t-tests using standard error estimates are consistent
     * with reported p-values
     */
    public void testStdErrorConsistency() throws Exception {
        TDistribution tDistribution = new TDistributionImpl(45);
        RealMatrix matrix = createRealMatrix(swissData, 47, 5);
        PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix); 
        RealMatrix rValues = corrInstance.getCorrelationMatrix();
        RealMatrix pValues = corrInstance.getCorrelationPValues();
        RealMatrix stdErrors = corrInstance.getCorrelationStandardErrors();
        for (int i = 0; i < 5; i++) {
            for (int j = 0; j < i; j++) {
                double t = Math.abs(rValues.getEntry(i, j)) / stdErrors.getEntry(i, j);
                double p = 2 * (1 - tDistribution.cumulativeProbability(t));
                assertEquals(p, pValues.getEntry(i, j), 10E-15);
            }
        }
    }

View Full Code Here


    /**
     * Create an empty SimpleRegression instance
     */
    public SimpleRegression() {
        this(new TDistributionImpl(1.0));
    }

View Full Code Here

   * 
   * @return
   */
  public static Double tDistCDF(double x, int dof)
  {
    TDistributionImpl tdist = new TDistributionImpl(dof);
    try
    {
      return tdist.cumulativeProbability(x);
    }
    catch (MathException e)
    {
      e.printStackTrace();
    }

View Full Code Here

  /**
   * For this distribution, X, this method returns the critical point x, such that P(X < x) = p. Returns Double.NEGATIVE_INFINITY for p=0 and Double.POSITIVE_INFINITY for p=1.
   */
  public static Double tDistInverseCDF(double p_value, int dof)
  {
    TDistributionImpl tdist = new TDistributionImpl(dof);
    try
    {
      return tdist.inverseCumulativeProbability(p_value);
    }
    catch (MathException e)
    {
      e.printStackTrace();
    }

View Full Code Here

     *
     * @return matrix of p-values
     * @throws MathException if an error occurs estimating probabilities
     */
    public RealMatrix getCorrelationPValues() throws MathException {
        TDistribution tDistribution = new TDistributionImpl(nObs - 2);
        int nVars = correlationMatrix.getColumnDimension();
        double[][] out = new double[nVars][nVars];
        for (int i = 0; i < nVars; i++) {
            for (int j = 0; j < nVars; j++) {
                if (i == j) {
                    out[i][j] = 0d;
                } else {
                    double r = correlationMatrix.getEntry(i, j);
                    double t = Math.abs(r * Math.sqrt((nObs - 2)/(1 - r * r)));
                    out[i][j] = 2 * (1 - tDistribution.cumulativeProbability(t));
                }
            }
        }
        return new BlockRealMatrix(out);
    }

View Full Code Here


    /**
     * Create an empty SimpleRegression instance
     */
    public SimpleRegression() {
        this(new TDistributionImpl(1.0));
    }

View Full Code Here

0 1 2

TOP

Related Classes of org.apache.commons.math.distribution.TDistributionImpl

com.opengamma.analytics.math.regression.OrdinaryLeastSquaresRegression

com.opengamma.analytics.math.regression.WeightedLeastSquaresRegression

miscellaneous.StatisticsUtility

org.apache.commons.math.random.RandomDataImpl

org.apache.commons.math.random.RandomDataTest

org.apache.commons.math.stat.correlation.PearsonsCorrelation

org.apache.commons.math.stat.correlation.PearsonsCorrelationTest

org.apache.commons.math.stat.inference.TTestImpl

org.apache.commons.math.stat.regression.SimpleRegression

org.greg.server.GregServer

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.