Example usage for org.apache.commons.math.distribution ChiSquaredDistributionImpl ChiSquaredDistributionImpl

Introduction

In this page you can find the example usage for org.apache.commons.math.distribution ChiSquaredDistributionImpl ChiSquaredDistributionImpl.

Prototype

public ChiSquaredDistributionImpl(double df) 

Source Link

Document

Create a Chi-Squared distribution with the given degrees of freedom.

Usage

From source file:org.renjin.Distributions.java

public static double dchisq(final double x, final double df, boolean log) {
    return d(new ChiSquaredDistributionImpl(df), x, log);
}

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From source file:org.renjin.Distributions.java

public static double pchisq(final double q, final double df, boolean lowerTail, boolean logP) {
    if (df == 0) {
        return p(new ChisquareZeroDfDistribution(), q, lowerTail, logP);
    } else {//from   www  .j  a v  a 2  s  .c  o m
        return p(new ChiSquaredDistributionImpl(df), q, lowerTail, logP);
    }
}

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From source file:org.renjin.Distributions.java

public static double qchisq(final double p, final double df, boolean lowerTail, boolean logP) {
    if (df == 0) {
        return q(new ChisquareZeroDfDistribution(), p, lowerTail, logP);
    } else {//from w  w  w .j a va  2s  . com
        return q(new ChiSquaredDistributionImpl(df), p, lowerTail, logP);
    }
}

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From source file:org.renjin.primitives.random.Distributions.java

public static double dchisq(@Recycle double x, @Recycle double df, boolean log) {
    return d(new ChiSquaredDistributionImpl(df), x, log);
}

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From source file:org.renjin.primitives.random.Distributions.java

public static double pchisq(@Recycle double q, @Recycle double df, boolean lowerTail, boolean logP) {
    return p(new ChiSquaredDistributionImpl(df), q, lowerTail, logP);
}

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From source file:org.renjin.primitives.random.Distributions.java

public static double qchisq(@Recycle double p, @Recycle double df, boolean lowerTail, boolean logP) {
    return q(new ChiSquaredDistributionImpl(df), p, lowerTail, logP);
}

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From source file:org.renjin.stats.internals.Distributions.java

@DataParallel
@Internal//  w  w w .  j a  v a  2 s .  co m
public static double dchisq(@Recycle double x, @Recycle double df, boolean log) {
    return d(new ChiSquaredDistributionImpl(df), x, log);
}

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From source file:org.renjin.stats.internals.Distributions.java

@DataParallel
@Internal/*from   ww w . ja  v  a 2 s. c  om*/
public static double pchisq(@Recycle double q, @Recycle double df, boolean lowerTail, boolean logP) {
    if (df == 0) {
        return p(new ChisquareZeroDfDistribution(), q, lowerTail, logP);
    } else {
        return p(new ChiSquaredDistributionImpl(df), q, lowerTail, logP);
    }
}

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From source file:org.renjin.stats.internals.Distributions.java

@DataParallel
@Internal/*from  ww w  . ja  v  a 2 s .c o m*/
public static double qchisq(@Recycle double p, @Recycle double df, boolean lowerTail, boolean logP) {
    if (df == 0) {
        return q(new ChisquareZeroDfDistribution(), p, lowerTail, logP);
    } else {
        return q(new ChiSquaredDistributionImpl(df), p, lowerTail, logP);
    }
}

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From source file:ubic.gemma.analysis.preprocess.batcheffects.BatchConfound.java

/**
 * @param ee//from www .  j a  v a  2s  .  c o  m
 * @param bioMaterialFactorMap
 * @param svdo
 */
private static Collection<BatchConfoundValueObject> factorBatchConfoundTest(ExpressionExperiment ee,
        Map<ExperimentalFactor, Map<Long, Double>> bioMaterialFactorMap) throws IllegalArgumentException {

    Map<Long, Long> batchMembership = new HashMap<Long, Long>();
    ExperimentalFactor batchFactor = null;
    Map<Long, Integer> batchIndexes = new HashMap<Long, Integer>();
    for (ExperimentalFactor ef : bioMaterialFactorMap.keySet()) {
        if (ExperimentalDesignUtils.isBatch(ef)) {
            batchFactor = ef;

            Map<Long, Double> bmToFv = bioMaterialFactorMap.get(batchFactor);

            if (bmToFv == null) {
                log.warn("No biomaterial --> factor value map for batch factor: " + batchFactor);
                continue;
            }

            int index = 0;
            for (FactorValue fv : batchFactor.getFactorValues()) {
                batchIndexes.put(fv.getId(), index++);
            }

            for (Long bmId : bmToFv.keySet()) {
                batchMembership.put(bmId, bmToFv.get(bmId).longValue());
            }
            break;
        }
    }

    HashSet<BatchConfoundValueObject> result = new HashSet<BatchConfoundValueObject>();
    if (batchFactor == null) {
        return result;
    }

    /*
     * Compare other factors to batches to look for confounds.
     */

    for (ExperimentalFactor ef : bioMaterialFactorMap.keySet()) {

        if (ef.equals(batchFactor))
            continue;

        Map<Long, Double> bmToFv = bioMaterialFactorMap.get(ef);
        int numBioMaterials = bmToFv.keySet().size();

        assert numBioMaterials > 0 : "No biomaterials for " + ef;

        double p = Double.NaN;
        double chiSquare = Double.NaN;
        int df;

        int numBatches = batchFactor.getFactorValues().size();
        if (ExperimentalDesignUtils.isContinuous(ef)) {

            DoubleArrayList factorValues = new DoubleArrayList(numBioMaterials);
            factorValues.setSize(numBioMaterials);

            IntArrayList batches = new IntArrayList(numBioMaterials);
            batches.setSize(numBioMaterials);

            int j = 0;
            for (Long bmId : bmToFv.keySet()) {

                assert factorValues.size() > 0 : "Biomaterial to factorValue is empty for " + ef;

                factorValues.set(j, bmToFv.get(bmId));
                long batch = batchMembership.get(bmId);
                batches.set(j, batchIndexes.get(batch));
                j++;
            }

            p = KruskalWallis.test(factorValues, batches);
            df = KruskalWallis.dof(factorValues, batches);
            chiSquare = KruskalWallis.kwStatistic(factorValues, batches);

            log.debug("KWallis\t" + ee.getId() + "\t" + ee.getShortName() + "\t" + ef.getId() + "\t"
                    + ef.getName() + "\t" + String.format("%.2f", chiSquare) + "\t" + df + "\t"
                    + String.format("%.2g", p) + "\t" + numBatches);
        } else {

            Map<Long, Integer> factorValueIndexes = new HashMap<Long, Integer>();
            int index = 0;
            for (FactorValue fv : ef.getFactorValues()) {
                factorValueIndexes.put(fv.getId(), index++);
            }
            Map<Long, Long> factorValueMembership = new HashMap<Long, Long>();

            for (Long bmId : bmToFv.keySet()) {
                factorValueMembership.put(bmId, bmToFv.get(bmId).longValue());
            }

            long[][] counts = new long[numBatches][ef.getFactorValues().size()];

            for (int i = 0; i < batchIndexes.size(); i++) {
                for (int j = 0; j < factorValueIndexes.size(); j++) {
                    counts[i][j] = 0;
                }
            }

            for (Long bm : bmToFv.keySet()) {
                long fv = factorValueMembership.get(bm);
                Long batch = batchMembership.get(bm);
                if (batch == null) {
                    log.warn("No batch membership for : " + bm);
                    continue;
                }
                int batchIndex = batchIndexes.get(batch);
                int factorIndex = factorValueIndexes.get(fv);
                counts[batchIndex][factorIndex]++;
            }

            ChiSquareTest cst = new ChiSquareTestImpl();

            try {
                chiSquare = cst.chiSquare(counts);
            } catch (IllegalArgumentException e) {
                log.warn("IllegalArgumentException exception computing ChiSq for : " + ef + "; Error was: "
                        + e.getMessage());
                chiSquare = Double.NaN;
            }

            df = (counts.length - 1) * (counts[0].length - 1);
            ChiSquaredDistribution distribution = new ChiSquaredDistributionImpl(df);

            if (!Double.isNaN(chiSquare)) {
                try {
                    p = 1.0 - distribution.cumulativeProbability(chiSquare);
                } catch (MathException e) {
                    log.warn("Math exception computing ChiSq probability for " + chiSquare + ": "
                            + e.getMessage());
                    p = Double.NaN;
                }
            }

            log.debug("ChiSq\t" + ee.getId() + "\t" + ee.getShortName() + "\t" + ef.getId() + "\t"
                    + ef.getName() + "\t" + String.format("%.2f", chiSquare) + "\t" + df + "\t"
                    + String.format("%.2g", p) + "\t" + numBatches);
        }

        BatchConfoundValueObject summary = new BatchConfoundValueObject(ee, ef, chiSquare, df, p, numBatches);

        result.add(summary);
    }
    return result;
}

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