Example usage for org.apache.commons.math.stat.correlation Covariance Covariance

Introduction

In this page you can find the example usage for org.apache.commons.math.stat.correlation Covariance Covariance.

Prototype

public Covariance() 

Source Link

Document

Create a Covariance with no data

Usage

From source file:com.clican.pluto.dataprocess.dpl.function.impl.Convariance.java

public Object calculate(List<Map<String, Object>> rowSet)
        throws CalculationException, PrefixAndSuffixException {
    if (rowSet.size() == 0) {
        throw new CalculationException("Convariance??");
    }//from   w  ww.  j  a v a2  s .c o m
    double[] estimateValueList = new double[rowSet.size()];
    double[] referValueList = new double[rowSet.size()];
    for (int i = 0; i < rowSet.size(); i++) {
        Map<String, Object> row = rowSet.get(i);
        Double estimateValue = estimateVectorPas.getValue(row);
        Double referValue = referVectorPas.getValue(row);
        estimateValueList[i] = estimateValue;
        referValueList[i] = referValue;
    }
    Covariance cov = new Covariance();
    double covValue = cov.covariance(referValueList, estimateValueList, false);
    return covValue;
}

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From source file:com.clican.pluto.dataprocess.dpl.function.impl.Beta.java

private double getBeta(double[] referValueList, double[] estimateValueList) {
    Variance var = new Variance(false);
    Covariance cov = new Covariance();
    double varValue = var.evaluate(referValueList);
    double covValue = cov.covariance(referValueList, estimateValueList, false);
    if (log.isDebugEnabled()) {
        log.debug("Covariance=[" + covValue + "],Variance=[" + varValue + "]");
    }//from  ww w . j  ava  2s. c  o  m
    Double beta = covValue / varValue;
    return beta;
}

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From source file:com.srotya.sidewinder.core.analytics.TestMathUtils.java

@Test
public void testCovariance() {
    double[] a = new double[] { 2, 3, 4, 5, 6 };
    double[] b = new double[] { 2.2, 33.2, 44.4, 55.5, 66.6 };
    Covariance cov = new Covariance();
    double covariance = cov.covariance(a, b, false);
    double amean = MathUtils.mean(a);
    double bmean = MathUtils.mean(b);
    assertEquals(covariance, MathUtils.covariance(a, amean, b, bmean), 0.001);
}

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From source file:org.rascalmpl.library.analysis.statistics.Correlations.java

public IValue covariance(IList dataValues) {
    make(dataValues);
    return values.real(new Covariance().covariance(xvalues, yvalues, false));
}

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