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

                           final int begin, final int length) {
        if (test(values, weights, begin, length)) {
            Sum sum = new Sum();


            // Compute initial estimate using definitional formula
            double sumw = sum.evaluate(weights,begin,length);
            double xbarw = sum.evaluate(values, weights, begin, length) / sumw;


            // Compute correction factor in second pass
            double correction = 0;
            for (int i = begin; i < begin + length; i++) {

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        if (test(values, weights, begin, length)) {
            Sum sum = new Sum();


            // Compute initial estimate using definitional formula
            double sumw = sum.evaluate(weights,begin,length);
            double xbarw = sum.evaluate(values, weights, begin, length) / sumw;


            // Compute correction factor in second pass
            double correction = 0;
            for (int i = begin; i < begin + length; i++) {
                correction += weights[i] * (values[i] - xbarw);

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        if (test(values, begin, length)) {
            Sum sum = new Sum();
            double sampleSize = length;


            // Compute initial estimate using definitional formula
            double xbar = sum.evaluate(values, begin, length) / sampleSize;


            // Compute correction factor in second pass
            double correction = 0;
            for (int i = begin; i < begin + length; i++) {
                correction += values[i] - xbar;

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                           final int begin, final int length) throws MathIllegalArgumentException {
        if (test(values, weights, begin, length)) {
            Sum sum = new Sum();


            // Compute initial estimate using definitional formula
            double sumw = sum.evaluate(weights,begin,length);
            double xbarw = sum.evaluate(values, weights, begin, length) / sumw;


            // Compute correction factor in second pass
            double correction = 0;
            for (int i = begin; i < begin + length; i++) {

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        if (test(values, weights, begin, length)) {
            Sum sum = new Sum();


            // Compute initial estimate using definitional formula
            double sumw = sum.evaluate(weights,begin,length);
            double xbarw = sum.evaluate(values, weights, begin, length) / sumw;


            // Compute correction factor in second pass
            double correction = 0;
            for (int i = begin; i < begin + length; i++) {
                correction += weights[i] * (values[i] - xbarw);

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                    return 1.0;
                }
            };
            ret = FastMath.exp((a * FastMath.log(x)) + (b * FastMath.log1p(-x)) -
                FastMath.log(a) - logBeta(a, b)) *
                1.0 / fraction.evaluate(x, epsilon, maxIterations);
        }


        return ret;
    }

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                protected double getB(int n, double x) {
                    return n * (a - n);
                }
            };


            ret = 1.0 / cf.evaluate(x, epsilon, maxIterations);
            ret = FastMath.exp(-x + (a * FastMath.log(x)) - logGamma(a)) * ret;
        }


        return ret;
    }

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                    return 1.0;
                }
            };
            ret = FastMath.exp((a * FastMath.log(x)) + (b * FastMath.log(1.0 - x)) -
                FastMath.log(a) - logBeta(a, b, epsilon, maxIterations)) *
                1.0 / fraction.evaluate(x, epsilon, maxIterations);
        }


        return ret;
    }

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                protected double getB(int n, double x) {
                    return n * (a - n);
                }
            };


            ret = 1.0 / cf.evaluate(x, epsilon, maxIterations);
            ret = FastMath.exp(-x + (a * FastMath.log(x)) - logGamma(a)) * ret;
        }


        return ret;
    }

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                    return 1.0;
                }
            };
            ret = FastMath.exp((a * FastMath.log(x)) + (b * FastMath.log1p(-x)) -
                FastMath.log(a) - logBeta(a, b)) *
                1.0 / fraction.evaluate(x, epsilon, maxIterations);
        }


        return ret;
    }

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