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

Introduction

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

Prototype

public double cumulativeProbability(double x)

Source Link

Usage

From source file:wsattacker.library.intelligentdos.success.TTestSuccessDecider.java

private double calculateProbability(Long[] run1, Long[] run2) {
    SummaryStatistics statisticsX = new SummaryStatistics();
    for (double value : run1) {
        statisticsX.addValue(value);//  w w  w  .  j av  a 2s  .c o m
    }

    SummaryStatistics statisticsY = new SummaryStatistics();
    for (double value : run2) {
        statisticsY.addValue(value);
    }

    // two-sample
    double t = TestUtils.t(statisticsX, statisticsY);
    long degreesOfFreedom = statisticsX.getN() + statisticsY.getN() - 2;
    // p-value = 0.3002
    TDistribution tDistribution = new TDistribution(degreesOfFreedom);
    double pValue = tDistribution.cumulativeProbability(t);
    return pValue;
}

From source file:wsattacker.plugin.intelligentdos.StatisticTest.java

private static void statistics(double[] x, double[] y) {

    DecimalFormat df = new DecimalFormat("#.######");

    SummaryStatistics statisticsX = new SummaryStatistics();
    for (double value : x) {
        statisticsX.addValue(value);//from  w  w  w. ja  va  2s. c  o  m
    }

    SummaryStatistics statisticsY = new SummaryStatistics();
    for (double value : y) {
        statisticsY.addValue(value);
    }

    // t = -0.5331
    double t = TestUtils.t(statisticsX, statisticsY);
    // df = 18
    long degreesOfFreedom = statisticsX.getN() + statisticsY.getN() - 2;
    // p-value = 0.3002
    TDistribution tDistribution = new TDistribution(degreesOfFreedom);
    double pValue = tDistribution.cumulativeProbability(t);

    // t = -0.5331, df = 18, p-value = 0.3002
    System.out.print("t = " + df.format(t));
    System.out.print(", df = " + degreesOfFreedom);
    System.out.println(", p-value = " + df.format(pValue));

    System.out.println("mean of x mean of y");
    System.out.println(df.format(statisticsX.getMean()) + " - " + df.format(statisticsY.getMean()));

    // Calculate 95% confidence interval
    double ci = calcMeanCI(statisticsY, 0.95);
    System.out.println(String.format("Confidence inteval 95%%: %f", ci));
}