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

Examples of org.apache.commons.math3.stat.descriptive.moment.Mean.increment()

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        VectorialMean meanStat = new VectorialMean(mean.length);
        VectorialCovariance covStat = new VectorialCovariance(mean.length, true);
        for (int i = 0; i < 5000; ++i) {
            double[] v = generator.nextVector();
            meanStat.increment(v);
            covStat.increment(v);
        }

        double[] estimatedMean = meanStat.getResult();
        RealMatrix estimatedCovariance = covStat.getResult();
        for (int i = 0; i < estimatedMean.length; ++i) {
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        VectorialMean meanStat = new VectorialMean(mean.length);
        VectorialCovariance covStat = new VectorialCovariance(mean.length, true);
        for (int i = 0; i < 5000; ++i) {
            double[] v = generator.nextVector();
            meanStat.increment(v);
            covStat.increment(v);
        }

        double[] estimatedMean = meanStat.getResult();
        RealMatrix estimatedCovariance = covStat.getResult();
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        VectorialMean meanStat = new VectorialMean(mean.length);
        VectorialCovariance covStat = new VectorialCovariance(mean.length, true);
        for (int i = 0; i < 10000; ++i) {
            double[] v = generator.nextVector();
            meanStat.increment(v);
            covStat.increment(v);
        }

        double[] estimatedMean = meanStat.getResult();
        double scale;
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        VectorialMean meanStat = new VectorialMean(mean.length);
        VectorialCovariance covStat = new VectorialCovariance(mean.length, true);
        for (int i = 0; i < 5000; ++i) {
            double[] v = generator.nextVector();
            meanStat.increment(v);
            covStat.increment(v);
        }

        double[] estimatedMean = meanStat.getResult();
        RealMatrix estimatedCovariance = covStat.getResult();
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            final int nextInt = r.nextInt(100000000);
            secondMoment.increment(nextInt);
            sum.increment(nextInt);
            sumsq.increment(nextInt);
            min.increment(nextInt);
            max.increment(nextInt);
            sumLog.increment(nextInt);
        }

        testStorelessUnivariateStatistic(secondMoment, 7.513432791665536E15);
        testStorelessUnivariateStatistic(sum, 6.01312177E8);
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        for (int i = 0; i < 10; i++) {
            final int nextInt = r.nextInt(100000000);
            secondMoment.increment(nextInt);
            sum.increment(nextInt);
            sumsq.increment(nextInt);
            min.increment(nextInt);
            max.increment(nextInt);
            sumLog.increment(nextInt);
        }

        testStorelessUnivariateStatistic(secondMoment, 7.513432791665536E15);
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            for (int i = 0; i < data.length; i++) {
                double val = data[i];

                // within category
                num++;
                sum.increment(val);
                sumsq.increment(val);

                // for all categories
                totnum++;
                totsum.increment(val);
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            for (int i = 0; i < data.length; i++) {
                double val = data[i];

                // within category
                num++;
                sum.increment(val);
                sumsq.increment(val);

                // for all categories
                totnum++;
                totsum.increment(val);
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        final Random r = new Random(0);
        for (int i = 0; i < 10; i++) {
            final int nextInt = r.nextInt(100000000);
            secondMoment.increment(nextInt);
            sum.increment(nextInt);
            sumsq.increment(nextInt);
            min.increment(nextInt);
            max.increment(nextInt);
            sumLog.increment(nextInt);
        }
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            secondMoment.increment(nextInt);
            sum.increment(nextInt);
            sumsq.increment(nextInt);
            min.increment(nextInt);
            max.increment(nextInt);
            sumLog.increment(nextInt);
        }

        testStorelessUnivariateStatistic(secondMoment, 7.513432791665536E15);
        testStorelessUnivariateStatistic(sum, 6.01312177E8);
        testStorelessUnivariateStatistic(sumsq, 4.3671066212513456E16);
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