Example usage for org.apache.commons.math3.stat.inference TestUtils kolmogorovSmirnovTest

Introduction

In this page you can find the example usage for org.apache.commons.math3.stat.inference TestUtils kolmogorovSmirnovTest.

Prototype

public static double kolmogorovSmirnovTest(double[] x, double[] y, boolean strict)
        throws InsufficientDataException, NullArgumentException 

Source Link

Usage

From source file:iac_soap.statsq.NormVerdService.java

@Override
public NormVerdResponse calculateNormVerd(List<Double> data) throws MyFault {

    //Service Requirements 
    if (data.isEmpty()) {
        throw new MyFault("No data is provided");
    } else if (data.size() < 2) {
        throw new MyFault("A minimum of two data elements is required.");
    }//from ww  w.j  a  v  a2  s . c  o  m

    //Declaring Apache Commons DescriptiveStatistics
    DescriptiveStatistics stats = new DescriptiveStatistics();

    //Filling DescriptiveStatistics class with the provided dataset
    for (int i = 0; i < data.size(); i++) {
        stats.addValue(data.get(i));
    }

    //Let the DescriptiveStatistics class calculate the mean and standard deviation
    double mean = stats.getMean();
    double std = stats.getStandardDeviation();

    //Implementing the KolmogorovSmirnov test & calculating the kurtosis and skewness
    NormalDistribution x = new NormalDistribution(mean, std);
    double p_value = TestUtils.kolmogorovSmirnovTest(x, stats.getValues(), false);
    double kurtosis = stats.getKurtosis();
    double skewness = stats.getSkewness();
    boolean result = false;

    //Check if the dataset is a normal distribution:
    //KolmogorovSmirnov p_value should be >= 0.05
    //Both kurtosis and skewness should be between -2.0 and 2.0
    if (kurtosis < 2.0 && kurtosis > -2.0 && skewness < 2.0 && skewness > -2.0 && p_value >= 0.05) {
        result = true;
    }

    //Response message:
    NormVerdResponse nvr = new NormVerdResponse(result, p_value, kurtosis, skewness);

    return nvr;
}

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