Example usage for org.apache.commons.math3.distribution NormalDistribution cumulativeProbability

Introduction

In this page you can find the example usage for org.apache.commons.math3.distribution NormalDistribution cumulativeProbability.

Prototype

public double cumulativeProbability(double x)

Source Link

Document

If x is more than 40 standard deviations from the mean, 0 or 1 is returned, as in these cases the actual value is within Double.MIN_VALUE of 0 or 1.

Usage

From source file:uk.ac.diamond.scisoft.ncd.core.data.stats.AndersonDarlingNormalityTest.java

public boolean acceptNullHypothesis(Dataset data) {
    Dataset sortedData = data.clone().sort(null);
    double mean = (Double) data.mean(true);
    int size = data.getSize();
    double std = (Double) data.stdDeviation();
    //double std = Math.min((Double) errors.mean(true), (Double) data.stdDeviation());
    //double std = (Double) errors.mean(true);

    double thres = criticalValue / (1.0 + 4.0 / size - 25.0 / size / size);
    if (std > 0) {
        NormalDistribution norm = new NormalDistribution(mean, std);
        double sum = 0.0;
        for (int i = 0; i < size; i++) {
            double val1 = sortedData.getDouble(i);
            double val2 = sortedData.getDouble(size - 1 - i);
            double cdf1 = norm.cumulativeProbability(val1);
            double cdf2 = norm.cumulativeProbability(val2);
            sum += (2 * i + 1) * (Math.log(cdf1) + Math.log(1.0 - cdf2));
        }/*  w  ww  .  ja va 2s.c o  m*/
        double A2 = -size - sum / size;
        return (A2 < 0 ? true : (Math.sqrt(A2) < thres));
    }
    return true;
}

From source file:util.Statistics.java

public Statistics(List<Integer> list) {
    scores = intsToDoubles(list);/*from ww  w  .j  a v a  2 s . com*/
    DescriptiveStatistics dStats = new DescriptiveStatistics(scores);

    summaryStatistics.put("min", dStats.getMin()); // Minimum
    summaryStatistics.put("q1", dStats.getPercentile(25)); // Lower Quartile (Q1)
    summaryStatistics.put("q2", dStats.getPercentile(50)); // Middle Quartile (Median - Q2)
    summaryStatistics.put("q3", dStats.getPercentile(75)); // High Quartile (Q3)
    summaryStatistics.put("max", dStats.getMax()); // Maxiumum

    summaryStatistics.put("mean", dStats.getMean()); // Mean
    summaryStatistics.put("sd", dStats.getStandardDeviation()); // Standard Deviation

    EmpiricalDistribution distribution = new EmpiricalDistribution(NUM_BINS);
    distribution.load(scores);
    List<SummaryStatistics> binStats = distribution.getBinStats();
    double[] upperBounds = distribution.getUpperBounds();

    Double lastUpperBound = upperBounds[0];
    bins.add(new Pair<Pair<Double, Double>, Long>(
            new Pair<Double, Double>(summaryStatistics.get("min"), lastUpperBound), binStats.get(0).getN()));
    for (int i = 1; i < binStats.size(); i++) {
        bins.add(new Pair<Pair<Double, Double>, Long>(new Pair<Double, Double>(lastUpperBound, upperBounds[i]),
                binStats.get(i).getN()));
        lastUpperBound = upperBounds[i];
    }

    if (list.size() > 5 && dStats.getStandardDeviation() > 0) // Only remove outliers if relatively normal
    {
        double mean = dStats.getMean();
        double stDev = dStats.getStandardDeviation();
        NormalDistribution normalDistribution = new NormalDistribution(mean, stDev);

        Iterator<Integer> listIterator = list.iterator();
        double significanceLevel = .50 / list.size(); // Chauvenet's Criterion for Outliers
        while (listIterator.hasNext()) {
            int num = listIterator.next();
            double pValue = normalDistribution.cumulativeProbability(num);
            if (pValue < significanceLevel) {
                outliers.add(num);
                listIterator.remove();
            }
        }

        if (list.size() != dStats.getN()) // If and only if outliers have been removed
        {
            double[] significantData = intsToDoubles(list);
            dStats = new DescriptiveStatistics(significantData);

            summaryStatistics.put("min", dStats.getMin());
            summaryStatistics.put("max", dStats.getMax());
            summaryStatistics.put("mean", dStats.getMean());
            summaryStatistics.put("sd", dStats.getStandardDeviation());
        }
    }
}