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

Introduction

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

Prototype

public static DistributionFactory newInstance() 

Source Link

Document

Create an instance of a DistributionFactory

Usage

From source file:de.tud.kom.p2psim.impl.util.stats.ConfidenceInterval.java

/**
 * Returns the delta between the mean and the lower(x1)/upper(x2) bound as
 * positive number. That is, the probabilistic bounds of x1 and x2 are given
 * by x1 <= mean <= x2 <=> mean-delta <= mean <= mean + delta
 * //www  . j ava 2 s  .  c om
 * @param sdev
 *            the given standard deviation
 * @param n
 *            the given sample size
 * @param alpha
 *            the given significance level
 * @return the upper/lower bound as positiv number
 */
public static double getDeltaBound(double sdev, int n, double alpha) {
    TDistribution tDist = DistributionFactory.newInstance().createTDistribution(n - 1);
    double errorConfCoeff = 1d - (alpha / 2);
    double delta;
    try {
        double t = Math.abs(tDist.inverseCumulativeProbability(errorConfCoeff));
        delta = t * sdev / Math.sqrt(n);
    } catch (MathException e) {
        throw new IllegalStateException(e);
    }
    return delta;
}

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From source file:clus.statistic.RegressionStatBase.java

/**
 * Computes a 2-sample t statistic, without the hypothesis of equal sub-population variances,
 * and returns the p-value of a t test.//from   w  ww  .ja  v a  2  s .c o m
 * t = (m1 - m2) / sqrt(var1/n1 + var2/n2);
 * @param att attribute index
 * @return t p-value
 * @throws MathException
 */
public double getTTestPValue(int att, ClusStatManager stat_manager) throws MathException {
    double global_mean = ((CombStat) stat_manager.getTrainSetStat()).m_RegStat.getMean(att);
    double global_var = ((CombStat) stat_manager.getTrainSetStat()).m_RegStat.getVariance(att);
    double global_n = ((CombStat) stat_manager.getTrainSetStat()).getTotalWeight();
    double local_mean = getMean(att);
    double local_var = getVariance(att);
    double local_n = getTotalWeight();
    double t = Math.abs(local_mean - global_mean) / Math.sqrt(local_var / local_n + global_var / global_n);
    double degreesOfFreedom = 0;
    degreesOfFreedom = df(local_var, global_var, local_n, global_n);
    DistributionFactory distributionFactory = DistributionFactory.newInstance();
    TDistribution tDistribution = distributionFactory.createTDistribution(degreesOfFreedom);
    return 1.0 - tDistribution.cumulativeProbability(-t, t);
}

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From source file:clus.pruning.C45Pruner.java

public double computeZScore() throws ClusException {
    try {/*  www .jav a  2s.c  o m*/
        DistributionFactory distributionFactory = DistributionFactory.newInstance();
        return distributionFactory.createNormalDistribution()
                .inverseCumulativeProbability(1 - m_ConfidenceFactor);
    } catch (MathException e) {
        throw new ClusException(e.getMessage());
    }
}

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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))//from   w  w  w .  ja  v a  2  s. c om
 * @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.//from   w w w . j a  va2s.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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