Example usage for org.apache.commons.math3.stat.descriptive.rank Percentile Percentile

Introduction

In this page you can find the example usage for org.apache.commons.math3.stat.descriptive.rank Percentile Percentile.

Prototype

public Percentile()

Source Link

Document

Constructs a Percentile with a default quantile value of 50.0.

Usage

From source file:com.itemanalysis.psychometrics.statistics.Bootstrap.java

public Bootstrap(double lower, double upper) {
    this.lower = lower;
    this.upper = upper;
    percentile = new Percentile();
    stdDev = new StandardDeviation();
}

From source file:com.itemanalysis.psychometrics.statistics.Deciles.java

private void intialize() {
    for (int i = 0; i < size; i++) {
        q[i] = new Percentile();
    }
}

From source file:com.itemanalysis.psychometrics.kernel.ScottsBandwidth.java

public ScottsBandwidth(double[] x, double adjustmentFactor) {
    this.x = x;//from  w  w  w  . j  a  va 2  s  .  c  o  m
    this.adjustmentFactor = adjustmentFactor;
    pcntl = new Percentile();
}

From source file:com.github.rvesse.github.pr.stats.collectors.LongStatsCollector.java

@Override
public void end() {
    double[] ds = toDoubles();

    // Populate percentiles
    this.percentiles = new Percentile();
    this.percentiles.setData(ds);
}

From source file:com.itemanalysis.psychometrics.irt.equating.RobustZEquatingTest.java

/**
 * Constructor for use with 2PL and 3PL models.
 *
 * @param aX// w  ww .j av  a  2  s . c o  m
 * @param aY
 * @param bX
 * @param bY
 * @param significanceLevel
 * @throws IllegalArgumentException
 */
public RobustZEquatingTest(double[] aX, double[] aY, double[] bX, double[] bY, double significanceLevel)
        throws IllegalArgumentException {
    if (aX.length != aY.length || bX.length != bY.length) {
        throw new IllegalArgumentException("Item parameter arrays must be the same length");
    }

    this.aX = aX;
    this.aY = aY;
    this.bX = bX;
    this.bY = bY;
    nA = aX.length;
    nB = bX.length;
    this.significanceLevel = significanceLevel / 2.0;

    percentile = new Percentile();
    if (hasDiscriminationParameters()) {
        modelParams = 2;
        testA();
    } else {
        modelParams = 1;
    }
    testB();
}

From source file:inflor.core.transforms.LogicleTransform.java

private double optimizeW(double[] data) {
    /**//from   w w w.j  a  v a  2  s  .c o m
     * Based on the percentile method suggested by Parks/Moore.
     */
    double lowerBound = new Percentile().evaluate(data, LOGICLE_W_PERCENTILE);
    if (lowerBound < 0) {
        this.w = (m - Math.log10(t / Math.abs(lowerBound))) / 2;
    } else {
        this.w = 0.2;//TODO: Reasonable?
    }
    //TODO HACKZ
    if (w <= 0)
        w = 0.2;
    return w;
}

From source file:inflor.core.transforms.BoundDisplayTransform.java

public void optimize(double[] data) {
    this.boundaryMin = new Percentile().evaluate(data, LOWER_BOUND_PERCENT);
    this.boundaryMax = new Percentile().evaluate(data, UPPER_BOUND_PERCENT);
}

From source file:com.cidre.algorithms.CidreMath.java

public static double[] zLimitsFromPercentiles(double[] values) {
    double[] zLimits = new double[2];
    Percentile p = new Percentile();
    p.setData(values);/* www.  j a  v  a  2s.c om*/
    zLimits[0] = p.evaluate(0.1);
    zLimits[1] = p.evaluate(99.9);
    log.debug("zLimits {}, {}", zLimits[0], zLimits[1]);
    return zLimits;
}

From source file:com.itemanalysis.psychometrics.irt.equating.RobustZEquatingTest.java

/**
 * Constructor for use with Rasch or 1PL model
 * @param bX// w  w w .  j  a v a 2s.  c om
 * @param bY
 * @param significanceLevel
 * @throws IllegalArgumentException
 */
public RobustZEquatingTest(double[] bX, double[] bY, double significanceLevel) throws IllegalArgumentException {
    nB = bX.length;
    if (nB != bX.length || nB != bY.length) {
        throw new IllegalArgumentException("Item parameter arrays must be the same length");
    }
    this.bX = bX;
    this.bY = bY;
    this.significanceLevel = significanceLevel;
    modelParams = 1;
    percentile = new Percentile();
    testB();
}

From source file:com.mgmtp.perfload.perfalyzer.binning.PerfMonBinningStrategy.java

private void writeAggregatedLine(final WritableByteChannel destChannel) throws IOException {
    double[] allValues = binManager.flatValuesStream().toArray();

    StrBuilder sb = new StrBuilder();

    String min = intNumberFormat.format(Doubles.min(allValues));
    String max = intNumberFormat.format(Doubles.max(allValues));

    switch (typeConfig) {
    case CPU://from   w w  w .  j a va2s.c o m
    case IO:
    case JAVA:
        String mean = intNumberFormat.format(StatUtils.mean(allValues));
        appendEscapedAndQuoted(sb, DELIMITER, min, mean, max);
        break;
    case MEM:
    case SWAP:
        Percentile percentile = new Percentile();
        percentile.setData(allValues);
        String q10 = intNumberFormat.format(percentile.evaluate(10d));
        String q50 = intNumberFormat.format(percentile.evaluate(50d));
        String q90 = intNumberFormat.format(percentile.evaluate(90d));
        appendEscapedAndQuoted(sb, DELIMITER, min, q10, q50, q90, max);
        break;
    default:
        throw new IllegalStateException("Invalid perfMon data type");
    }

    writeLineToChannel(destChannel, sb.toString(), Charsets.UTF_8);
}