Examples of org.apache.commons.math3.stat.descriptive.rank.Median.evaluate()

Package org.apache.commons.math3.stat.descriptive.rank

Class org.apache.commons.math3.stat.descriptive.rank.Median

Examples of org.apache.commons.math3.stat.descriptive.rank.Median.evaluate()

org.apache.commons.math3.stat.descriptive.rank.Median.evaluate()
Returns the result of evaluating the statistic over the input array, using the supplied weights. @param values input array @param weights array of weights @return the value of the weighted statistic applied to the input array @throws MathIllegalArgumentException if either array is null, lengthsdo not match, weights contain NaN, negative or infinite values, or weights does not include at least on positive value

                  LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, length, yArray.length);
        } else if (length < 2) {
            throw new MathIllegalArgumentException(
                  LocalizedFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE, length, 2);
        } else {
            double xMean = mean.evaluate(xArray);
            double yMean = mean.evaluate(yArray);
            for (int i = 0; i < length; i++) {
                double xDev = xArray[i] - xMean;
                double yDev = yArray[i] - yMean;
                result += (xDev * yDev - result) / (i + 1);

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        } else if (length < 2) {
            throw new MathIllegalArgumentException(
                  LocalizedFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE, length, 2);
        } else {
            double xMean = mean.evaluate(xArray);
            double yMean = mean.evaluate(yArray);
            for (int i = 0; i < length; i++) {
                double xDev = xArray[i] - xMean;
                double yDev = yArray[i] - yMean;
                result += (xDev * yDev - result) / (i + 1);
            }

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                  LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, length, yArray.length);
        } else if (length < 2) {
            throw new MathIllegalArgumentException(
                  LocalizedFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE, length, 2);
        } else {
            double xMean = mean.evaluate(xArray);
            double yMean = mean.evaluate(yArray);
            for (int i = 0; i < length; i++) {
                double xDev = xArray[i] - xMean;
                double yDev = yArray[i] - yMean;
                result += (xDev * yDev - result) / (i + 1);

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        } else if (length < 2) {
            throw new MathIllegalArgumentException(
                  LocalizedFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE, length, 2);
        } else {
            double xMean = mean.evaluate(xArray);
            double yMean = mean.evaluate(yArray);
            for (int i = 0; i < length; i++) {
                double xDev = xArray[i] - xMean;
                double yDev = yArray[i] - yMean;
                result += (xDev * yDev - result) / (i + 1);
            }

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        for (int i = 0; i < length; i++) {
            values[i] = start + i;
        }


        StandardDeviation stdDev = new StandardDeviation();
        return stdDev.evaluate(values);
    }


    @Override
    protected String getFunctionName()
    {

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        for (int i = 0; i < length; i++) {
            values[i] = start + i;
        }


        StandardDeviation stdDev = new StandardDeviation(false);
        return stdDev.evaluate(values);
    }


    @Override
    protected String getFunctionName()
    {

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        for (int i = 0; i < length; i++) {
            values[i] = start + i;
        }


        StandardDeviation stdDev = new StandardDeviation(false);
        return stdDev.evaluate(values);
    }


    @Override
    protected String getFunctionName()
    {

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        for (int i = 0; i < length; i++) {
            values[i] = start + i;
        }


        StandardDeviation stdDev = new StandardDeviation();
        return stdDev.evaluate(values);
    }


    @Override
    protected String getFunctionName()
    {

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        StandardDeviation standardDeviation = new StandardDeviation();
        System.out.println(label + ":");
        System.out.println(String.format("  mean : %.2f", StatUtils.mean(values)));
        System.out.println(String.format("  min  : %.2f", StatUtils.min(values)));
        System.out.println(String.format("  max  : %.2f", StatUtils.max(values)));
        System.out.println(String.format("  stdev: %.2f", standardDeviation.evaluate(values)));
        System.out.println("");
    }


    public enum Suit {
        SPADE, HEART, DIAMOND, CLUB;

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        for (int i = 0; i < length; i++) {
            values[i] = start + i;
        }


        StandardDeviation stdDev = new StandardDeviation();
        return stdDev.evaluate(values);
    }
}

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