Package org.apache.commons.math3.stat.ranking

Examples of org.apache.commons.math3.stat.ranking.NaturalRanking

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     * <p>Double.NaN is returned if no values have been added.</p>
     *
     * @return the population variance
     */
    public double getPopulationVariance() {
        Variance populationVariance = new Variance(secondMoment);
        populationVariance.setBiasCorrected(false);
        return populationVariance.getResult();
    }
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        dest.secondMoment = source.secondMoment.copy();
        dest.n = source.n;

        // Keep commons-math supplied statistics with embedded moments in synch
        if (source.getVarianceImpl() instanceof Variance) {
            dest.varianceImpl = new Variance(dest.secondMoment);
        } else {
            dest.varianceImpl = source.varianceImpl.copy();
        }
        if (source.meanImpl instanceof Mean) {
            dest.meanImpl = new Mean(dest.secondMoment);
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        for (int i = 0; i < k; ++i) {
            sumImpl[i]     = new Sum();
            sumSqImpl[i]   = new SumOfSquares();
            minImpl[i]     = new Min();
            maxImpl[i]     = new Max();
            sumLogImpl[i]  = new SumOfLogs();
            geoMeanImpl[i] = new GeometricMean();
            meanImpl[i]    = new Mean();
        }

        covarianceImpl =
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        geoMeanImpl = new StorelessUnivariateStatistic[k];
        meanImpl    = new StorelessUnivariateStatistic[k];

        for (int i = 0; i < k; ++i) {
            sumImpl[i]     = new Sum();
            sumSqImpl[i]   = new SumOfSquares();
            minImpl[i]     = new Min();
            maxImpl[i]     = new Max();
            sumLogImpl[i]  = new SumOfLogs();
            geoMeanImpl[i] = new GeometricMean();
            meanImpl[i]    = new Mean();
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    /**
     * Create a SpearmansCorrelation without data.
     */
    public SpearmansCorrelation() {
        this(new NaturalRanking());
    }
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     *
     * @param dataMatrix matrix of data with columns representing
     * variables to correlate
     */
    public SpearmansCorrelation(final RealMatrix dataMatrix) {
        this(dataMatrix, new NaturalRanking());
    }
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     * Create a test instance where NaN's are left in place and ties get
     * the average of applicable ranks. Use this unless you are very sure
     * of what you are doing.
     */
    public WilcoxonSignedRankTest() {
        naturalRanking = new NaturalRanking(NaNStrategy.FIXED,
                TiesStrategy.AVERAGE);
    }
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     * @param tiesStrategy
     *            specifies the strategy that should be used for ties
     */
    public WilcoxonSignedRankTest(final NaNStrategy nanStrategy,
                                  final TiesStrategy tiesStrategy) {
        naturalRanking = new NaturalRanking(nanStrategy, tiesStrategy);
    }
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     * Create a test instance using where NaN's are left in place and ties get
     * the average of applicable ranks. Use this unless you are very sure of
     * what you are doing.
     */
    public MannWhitneyUTest() {
        naturalRanking = new NaturalRanking(NaNStrategy.FIXED,
                TiesStrategy.AVERAGE);
    }
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     * @param tiesStrategy
     *            specifies the strategy that should be used for ties
     */
    public MannWhitneyUTest(final NaNStrategy nanStrategy,
                            final TiesStrategy tiesStrategy) {
        naturalRanking = new NaturalRanking(nanStrategy, tiesStrategy);
    }
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Related Classes of org.apache.commons.math3.stat.ranking.NaturalRanking

  • org.apache.commons.math3.analysis.differentiation.DerivativeStructure
  • org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction
  • org.apache.commons.math3.analysis.function.HarmonicOscillator
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.MultivariateFunction
  • org.apache.commons.math3.analysis.QuinticFunction
  • org.apache.commons.math3.analysis.solvers.BrentSolver
  • org.apache.commons.math3.analysis.UnivariateFunction
  • org.apache.commons.math3.complex.Complex
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