Example usage for org.apache.commons.math.stat.descriptive.moment Variance evaluate

Introduction

In this page you can find the example usage for org.apache.commons.math.stat.descriptive.moment Variance evaluate.

Prototype

public double evaluate(final double[] values, final double mean) 

Source Link

Document

Returns the variance of the entries in the input array, using the precomputed mean value.

Usage

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

public Object calculate(List<Map<String, Object>> rowSet)
        throws CalculationException, PrefixAndSuffixException {
    if (rowSet.size() == 0) {
        throw new CalculationException("SharpeRatio??");
    }/*from ww w .j  a  v a  2 s.  c  o  m*/
    double[] values = new double[rowSet.size()];
    double sum = 0;
    for (int i = 0; i < rowSet.size(); i++) {
        Map<String, Object> row = rowSet.get(i);
        Double value = valuePas.getValue(row);
        values[i] = value;
        sum += value;
    }
    double avg = sum / rowSet.size();
    Variance var = new Variance(false);
    return Math.sqrt(var.evaluate(values, avg));
}

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

public Object calculate(List<Map<String, Object>> rowSet)
        throws CalculationException, PrefixAndSuffixException {
    if (rowSet.size() == 0) {
        throw new CalculationException("SharpeRatio??");
    }/*from  w w  w  .  j ava 2  s  .  c om*/

    double[] values = new double[rowSet.size()];
    double sum = 0;
    for (int i = 0; i < rowSet.size(); i++) {
        Map<String, Object> row = rowSet.get(i);
        Double value = valuePas.getValue(row);
        values[i] = value;
        sum += value;
    }
    double avg = sum / (rowSet.size());
    Variance var = new Variance(false);
    Double result = Math.sqrt(var.evaluate(values, avg));
    if (log.isDebugEnabled()) {
        log.debug("FRR[" + avg + "],STDEV[" + result + "]");
    }
    return avg / result;
}

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

/**
 * @param rowSet/*from   w ww  . java  2 s .  c  om*/
 *            List
 * @see com.clican.pluto.dataprocess.dpl.function.MultiRowFunction#calculate(java.util.List)
 */

public Object calculate(List<Map<String, Object>> rowSet)
        throws CalculationException, PrefixAndSuffixException {
    if (rowSet == null || rowSet.size() == 0) {
        throw new CalculationException("??");
    }

    double[] values = new double[rowSet.size()];
    double sum = 0;
    for (int i = 0; i < rowSet.size(); i++) {
        Map<String, Object> row = rowSet.get(i);
        Double fundValue = fundNavList.getValue(row);
        Double indexValue = indexList.getValue(row);
        double value = fundValue.doubleValue() - indexValue.doubleValue();
        values[i] = value;
        sum += value;
    }
    double avg = sum / (rowSet.size());

    Variance var = new Variance(false);
    Double result = Math.sqrt(var.evaluate(values, avg));

    return result;
}

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

public Object calculate(List<Map<String, Object>> rowSet)
        throws CalculationException, PrefixAndSuffixException {
    if (rowSet.size() == 0) {
        throw new CalculationException("InformationRatio??");
    }/*from   www  .  j a va  2  s . c  om*/
    List<Double> estimateValueList = new ArrayList<Double>();
    List<Double> referValueList = new ArrayList<Double>();
    Double estimateSum = 0d;
    Double referSum = 0d;
    Double differencingSum = 0d;
    double[] differencingList = 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);
        Double differencing = estimateValue - referValue;
        estimateSum += estimateValue;
        referSum += referValue;
        differencingSum += differencing;
        estimateValueList.add(estimateSum);
        referValueList.add(referValue);
        differencingList[i] = differencing;
    }
    Double estimateAvg = estimateSum / estimateValueList.size();
    Double referAvg = referSum / referValueList.size();

    Variance var = new Variance(false);
    Double standard = Math.sqrt(var.evaluate(differencingList, differencingSum / differencingList.length));
    Double result = (estimateAvg - referAvg) / standard;
    if (log.isDebugEnabled()) {
        log.debug("FR=[" + estimateAvg + "],BR=[" + referAvg + "],=[" + standard + "],information=[" + result
                + "]");
    }
    return result;
}

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