Example usage for org.apache.commons.math.distribution DistributionFactory createChiSquareDistribution

Introduction

In this page you can find the example usage for org.apache.commons.math.distribution DistributionFactory createChiSquareDistribution.

Prototype

public abstract ChiSquaredDistribution createChiSquareDistribution(double degreesOfFreedom);

Source Link

Document

Create a new chi-square distribution with the given degrees of freedom.

Usage

From source file:clus.statistic.ClassificationStat.java

/**
 * Computes a G statistic and returns the p-value of a G test.
 * G = 2*SUM(obs*ln(obs/exp))//ww  w .j  a  va  2  s.c o m
 * @param att attribute index
 * @return p-value
 * @throws MathException
 */
public double getGTestPValue(int att, ClusStatManager stat_manager) throws MathException {
    double global_n = ((CombStat) stat_manager.getTrainSetStat()).getTotalWeight();
    double local_n = getTotalWeight();
    double ratio = local_n / global_n;
    double global_counts[] = ((CombStat) stat_manager.getTrainSetStat()).m_ClassStat.getClassCounts(att);
    double local_counts[] = getClassCounts(att);
    double g = 0;
    for (int i = 0; i < global_counts.length; i++) {
        if ((local_counts[i] > 0) && (global_counts[i] > 0)) {
            g += 2 * local_counts[i] * Math.log(local_counts[i] / (global_counts[i] * ratio));
        }
    }
    double degreesOfFreedom = ((double) global_counts.length) - 1;
    DistributionFactory distributionFactory = DistributionFactory.newInstance();
    ChiSquaredDistribution chiSquaredDistribution = distributionFactory
            .createChiSquareDistribution(degreesOfFreedom);
    return 1 - chiSquaredDistribution.cumulativeProbability(g);
}

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From source file:clus.main.ClusStatManager.java

/**
 * Initializes a table with Chi Squared inverse probabilities used in
 * significance testing of rules./*  w w w . ja v  a2 s .  c om*/
 *
 * @throws MathException
 *
 */
public void initSignifcanceTestingTable() {
    int max_nom_val = 0;
    int num_nom_atts = m_Schema.getNbNominalAttrUse(ClusAttrType.ATTR_USE_ALL);
    for (int i = 0; i < num_nom_atts; i++) {
        if (m_Schema.getNominalAttrUse(ClusAttrType.ATTR_USE_ALL)[i].m_NbValues > max_nom_val) {
            max_nom_val = m_Schema.getNominalAttrUse(ClusAttrType.ATTR_USE_ALL)[i].m_NbValues;
        }
    }
    if (max_nom_val == 0) { // If no nominal attributes in data set
        max_nom_val = 1;
    }
    double[] table = new double[max_nom_val];
    table[0] = 1.0 - getSettings().getRuleSignificanceLevel();
    // Not really used except below
    for (int i = 1; i < table.length; i++) {
        DistributionFactory distributionFactory = DistributionFactory.newInstance();
        ChiSquaredDistribution chiSquaredDistribution = distributionFactory.createChiSquareDistribution(i);
        try {
            table[i] = chiSquaredDistribution.inverseCumulativeProbability(table[0]);
        } catch (MathException e) {
            e.printStackTrace();
        }
    }
    m_ChiSquareInvProb = table;
}

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