Examples of NaturalRanking

org.apache.commons.math.stat.ranking.NaturalRanking

Ranking based on the natural ordering on doubles.

NaNs are treated according to the configured {@link NaNStrategy} and tiesare handled using the selected {@link TiesStrategy}. Configuration settings are supplied in optional constructor arguments. Defaults are {@link NaNStrategy#MAXIMAL} and {@link TiesStrategy#AVERAGE}, respectively. When using {@link TiesStrategy#RANDOM}, a {@link RandomGenerator} may be supplied as a constructor argument.

Examples:

Input data: (20, 17, 30, 42.3, 17, 50, Double.NaN, Double.NEGATIVE_INFINITY, 17)
NaNStrategy	TiesStrategy	`rank(data)`
default (NaNs maximal)	default (ties averaged)	(5, 3, 6, 7, 3, 8, 9, 1, 3)
default (NaNs maximal)	MINIMUM	(5, 2, 6, 7, 2, 8, 9, 1, 2)
MINIMAL	default (ties averaged)	(6, 4, 7, 8, 4, 9, 1.5, 1.5, 4)
REMOVED	SEQUENTIAL	(5, 2, 6, 7, 3, 8, 1, 4)
MINIMAL	MAXIMUM	(6, 5, 7, 8, 5, 9, 2, 2, 5)

@since 2.0 @version $Revision: 1061496 $ $Date: 2011-01-20 21:32:16 +0100 (jeu. 20 janv. 2011) $

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

Ranking based on the natural ordering on doubles.

NaNs are treated according to the configured {@link NaNStrategy} and tiesare handled using the selected {@link TiesStrategy}. Configuration settings are supplied in optional constructor arguments. Defaults are {@link NaNStrategy#FAILED} and {@link TiesStrategy#AVERAGE}, respectively. When using {@link TiesStrategy#RANDOM}, a {@link RandomGenerator} may be supplied as a constructor argument.

Examples:

Input data: (20, 17, 30, 42.3, 17, 50, Double.NaN, Double.NEGATIVE_INFINITY, 17)
NaNStrategy	TiesStrategy	`rank(data)`
default (NaNs maximal)	default (ties averaged)	(5, 3, 6, 7, 3, 8, 9, 1, 3)
default (NaNs maximal)	MINIMUM	(5, 2, 6, 7, 2, 8, 9, 1, 2)
MINIMAL	default (ties averaged)	(6, 4, 7, 8, 4, 9, 1.5, 1.5, 4)
REMOVED	SEQUENTIAL	(5, 2, 6, 7, 3, 8, 1, 4)
MINIMAL	MAXIMUM	(6, 5, 7, 8, 5, 9, 2, 2, 5)

@since 2.0

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

      ITuple T = (ITuple) dataValues.get(i);
      xvalues[i] = ((INumber) T.get(0)).toReal().doubleValue();
    }
    
    // Create a natural ranking: largest first.
    double rank[] = new NaturalRanking().rank(xvalues);
    
    for(int i = 0; i < rank.length; i++){
      rank[i] = rank.length - rank[i] + 1; // invert the ranking: smallest come now first.
      //System.err.println("rank[" + i + "] = " + rank[i]);
    }

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

     * 
     * @param dataMatrix matrix of data with columns representing
     * variables to correlate
     */
    public SpearmansCorrelation(final RealMatrix dataMatrix) {
        this(dataMatrix, new NaturalRanking());
    }

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

    /**
     * Create a SpearmansCorrelation without data.
     */
    public SpearmansCorrelation() {
        data = null; 
        this.rankingAlgorithm = new NaturalRanking();
        rankCorrelation = null;
    }

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

     *
     * @param dataMatrix matrix of data with columns representing
     * variables to correlate
     */
    public SpearmansCorrelation(final RealMatrix dataMatrix) {
        this(dataMatrix, new NaturalRanking());
    }

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

    /**
     * Create a SpearmansCorrelation without data.
     */
    public SpearmansCorrelation() {
        data = null;
        this.rankingAlgorithm = new NaturalRanking();
        rankCorrelation = null;
    }

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

     * 
     * @param dataMatrix matrix of data with columns representing
     * variables to correlate
     */
    public SpearmansCorrelation(final RealMatrix dataMatrix) {
        this(dataMatrix, new NaturalRanking());
    }

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

    /**
     * Create a SpearmansCorrelation without data.
     */
    public SpearmansCorrelation() {
        data = null; 
        this.rankingAlgorithm = new NaturalRanking();
        rankCorrelation = null;
    }

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

     *
     * @param dataMatrix matrix of data with columns representing
     * variables to correlate
     */
    public SpearmansCorrelation(final RealMatrix dataMatrix) {
        this(dataMatrix, new NaturalRanking());
    }

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

    /**
     * Create a SpearmansCorrelation without data.
     */
    public SpearmansCorrelation() {
        data = null;
        this.rankingAlgorithm = new NaturalRanking();
        rankCorrelation = null;
    }

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


    /**
     * Create a SpearmansCorrelation without data.
     */
    public SpearmansCorrelation() {
        this(new NaturalRanking());
    }

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