diff --git a/src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java b/src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java index 7f232c19c..4025f8484 100644 --- a/src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java +++ b/src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java @@ -226,7 +226,7 @@ public abstract class AbstractContinuousDistribution * @return lower bound of the support (might be Double.NEGATIVE_INFINITY) */ public abstract double getSupportLowerBound(); - + /** * Access the upper bound of the support. * diff --git a/src/main/java/org/apache/commons/math/distribution/AbstractDistribution.java b/src/main/java/org/apache/commons/math/distribution/AbstractDistribution.java index e7e8e7036..228b41fdb 100644 --- a/src/main/java/org/apache/commons/math/distribution/AbstractDistribution.java +++ b/src/main/java/org/apache/commons/math/distribution/AbstractDistribution.java @@ -35,16 +35,16 @@ public abstract class AbstractDistribution /** Cached numerical mean */ private double numericalMean = Double.NaN; - + /** Whether or not the numerical mean has been calculated */ private boolean numericalMeanIsCalculated = false; /** Cached numerical variance */ private double numericalVariance = Double.NaN; - + /** Whether or not the numerical variance has been calculated */ private boolean numericalVarianceIsCalculated = false; - + /** * Default constructor. */ @@ -77,18 +77,18 @@ public abstract class AbstractDistribution } return cumulativeProbability(x1) - cumulativeProbability(x0); } - + /** - * Use this method to actually calculate the mean for the - * specific distribution. Use {@link #getNumericalMean()} + * Use this method to actually calculate the mean for the + * specific distribution. Use {@link #getNumericalMean()} * (which implements caching) to actually get the mean. - * + * * @return the mean or Double.NaN if it's not defined */ protected abstract double calculateNumericalMean(); - + /** - * Use this method to get the numerical value of the mean of this + * Use this method to get the numerical value of the mean of this * distribution. * * @return the mean or Double.NaN if it's not defined @@ -101,22 +101,22 @@ public abstract class AbstractDistribution return numericalMean; } - + /** - * Use this method to actually calculate the variance for the - * specific distribution. Use {@link #getNumericalVariance()} - * (which implements caching) to actually get the variance. + * Use this method to actually calculate the variance for the + * specific distribution. Use {@link #getNumericalVariance()} + * (which implements caching) to actually get the variance. * * @return the variance or Double.NaN if it's not defined */ protected abstract double calculateNumericalVariance(); - + /** - * Use this method to get the numerical value of the variance of this + * Use this method to get the numerical value of the variance of this * distribution. * - * @return the variance (possibly Double.POSITIVE_INFINITY as - * for certain cases in {@link TDistributionImpl}) or + * @return the variance (possibly Double.POSITIVE_INFINITY as + * for certain cases in {@link TDistributionImpl}) or * Double.NaN if it's not defined */ public double getNumericalVariance() { @@ -124,40 +124,40 @@ public abstract class AbstractDistribution numericalVariance = calculateNumericalVariance(); numericalVarianceIsCalculated = true; } - + return numericalVariance; - } - + } + /** - * Use this method to get information about whether the lower bound + * Use this method to get information about whether the lower bound * of the support is inclusive or not. * * @return whether the lower bound of the support is inclusive or not */ public abstract boolean isSupportLowerBoundInclusive(); - + /** - * Use this method to get information about whether the upper bound + * Use this method to get information about whether the upper bound * of the support is inclusive or not. * * @return whether the upper bound of the support is inclusive or not */ - public abstract boolean isSupportUpperBoundInclusive(); - + public abstract boolean isSupportUpperBoundInclusive(); + /** - * Use this method to get information about whether the support is connected, + * Use this method to get information about whether the support is connected, * i.e. whether all values between the lower and upper bound of the support * is included in the support. - * + * * For {@link AbstractIntegerDistribution} the support is discrete, so - * if this is true, then the support is + * if this is true, then the support is * {lower bound, lower bound + 1, ..., upper bound}. - * + * * For {@link AbstractContinuousDistribution} the support is continuous, so * if this is true, then the support is the interval * [lower bound, upper bound] - * where the limits are inclusive or not according to - * {@link #isSupportLowerBoundInclusive()} and {@link #isSupportUpperBoundInclusive()} + * where the limits are inclusive or not according to + * {@link #isSupportLowerBoundInclusive()} and {@link #isSupportUpperBoundInclusive()} * (in the example both are true). If both are false, then the support is the interval * (lower bound, upper bound) * diff --git a/src/main/java/org/apache/commons/math/distribution/AbstractIntegerDistribution.java b/src/main/java/org/apache/commons/math/distribution/AbstractIntegerDistribution.java index 06a295b5f..0cb6331bb 100644 --- a/src/main/java/org/apache/commons/math/distribution/AbstractIntegerDistribution.java +++ b/src/main/java/org/apache/commons/math/distribution/AbstractIntegerDistribution.java @@ -290,42 +290,42 @@ public abstract class AbstractIntegerDistribution extends AbstractDistribution * @return the domain value upper bound, i.e. {@code P(X < 'upper bound') > p}. */ protected abstract int getDomainUpperBound(double p); - + /** * Access the lower bound of the support. * * @return lower bound of the support (Integer.MIN_VALUE for negative infinity) */ public abstract int getSupportLowerBound(); - + /** * Access the upper bound of the support. * * @return upper bound of the support (Integer.MAX_VALUE for positive infinity) */ public abstract int getSupportUpperBound(); - + /** - * Use this method to get information about whether the lower bound + * Use this method to get information about whether the lower bound * of the support is inclusive or not. For discrete support, * only true here is meaningful. * - * @return true (always but at Integer.MIN_VALUE because of the nature of discrete support) + * @return true (always but at Integer.MIN_VALUE because of the nature of discrete support) */ @Override public boolean isSupportLowerBoundInclusive() { return true; } - + /** - * Use this method to get information about whether the upper bound + * Use this method to get information about whether the upper bound * of the support is inclusive or not. For discrete support, * only true here is meaningful. * - * @return true (always but at Integer.MAX_VALUE because of the nature of discrete support) + * @return true (always but at Integer.MAX_VALUE because of the nature of discrete support) */ @Override public boolean isSupportUpperBoundInclusive() { return true; - } + } } diff --git a/src/main/java/org/apache/commons/math/distribution/BetaDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/BetaDistributionImpl.java index f18f9a6ea..57db81048 100644 --- a/src/main/java/org/apache/commons/math/distribution/BetaDistributionImpl.java +++ b/src/main/java/org/apache/commons/math/distribution/BetaDistributionImpl.java @@ -187,7 +187,7 @@ public class BetaDistributionImpl /** * {@inheritDoc} - * + * * The lower bound of the support is always 0 no matter the parameters. * * @return lower bound of the support (always 0) @@ -199,7 +199,7 @@ public class BetaDistributionImpl /** * {@inheritDoc} - * + * * The upper bound of the support is always 1 no matter the parameters. * * @return upper bound of the support (always 1) @@ -211,8 +211,8 @@ public class BetaDistributionImpl /** * {@inheritDoc} - * - * For first shape parameter s1 and + * + * For first shape parameter s1 and * second shape parameter s2, the mean is * s1 / (s1 + s2) * @@ -226,9 +226,9 @@ public class BetaDistributionImpl /** * {@inheritDoc} - * - * For first shape parameter s1 and - * second shape parameter s2, + * + * For first shape parameter s1 and + * second shape parameter s2, * the variance is * [ s1 * s2 ] / [ (s1 + s2)^2 * (s1 + s2 + 1) ] * @@ -237,7 +237,7 @@ public class BetaDistributionImpl @Override protected double calculateNumericalVariance() { final double a = getAlpha(); - final double b = getBeta(); + final double b = getBeta(); final double alphabetasum = a + b; return (a * b) / ((alphabetasum * alphabetasum) * (alphabetasum + 1)); } diff --git a/src/main/java/org/apache/commons/math/distribution/BinomialDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/BinomialDistributionImpl.java index dcea662de..346f7557d 100644 --- a/src/main/java/org/apache/commons/math/distribution/BinomialDistributionImpl.java +++ b/src/main/java/org/apache/commons/math/distribution/BinomialDistributionImpl.java @@ -167,8 +167,8 @@ public class BinomialDistributionImpl extends AbstractIntegerDistribution /** * {@inheritDoc} - * - * The lower bound of the support is always 0 no matter the number of trials + * + * The lower bound of the support is always 0 no matter the number of trials * and probability parameter. * * @return lower bound of the support (always 0) @@ -177,10 +177,10 @@ public class BinomialDistributionImpl extends AbstractIntegerDistribution public int getSupportLowerBound() { return 0; } - + /** * {@inheritDoc} - * + * * The upper bound of the support is the number of trials. * * @return upper bound of the support (equal to number of trials) @@ -192,8 +192,8 @@ public class BinomialDistributionImpl extends AbstractIntegerDistribution /** * {@inheritDoc} - * - * For n number of trials and + * + * For n number of trials and * probability parameter p, the mean is * n * p * @@ -206,8 +206,8 @@ public class BinomialDistributionImpl extends AbstractIntegerDistribution /** * {@inheritDoc} - * - * For n number of trials and + * + * For n number of trials and * probability parameter p, the variance is * n * p * (1 - p) * diff --git a/src/main/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java index ef0fc7d90..ac3760f56 100644 --- a/src/main/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java +++ b/src/main/java/org/apache/commons/math/distribution/CauchyDistributionImpl.java @@ -163,7 +163,7 @@ public class CauchyDistributionImpl extends AbstractContinuousDistribution } return ret; - } + } /** * Access the domain value upper bound, based on p, used to @@ -223,8 +223,8 @@ public class CauchyDistributionImpl extends AbstractContinuousDistribution /** * {@inheritDoc} - * - * The lower bound of the support is always negative infinity no matter + * + * The lower bound of the support is always negative infinity no matter * the parameters. * * @return lower bound of the support (always Double.NEGATIVE_INFINITY) @@ -236,8 +236,8 @@ public class CauchyDistributionImpl extends AbstractContinuousDistribution /** * {@inheritDoc} - * - * The upper bound of the support is always positive infinity no matter + * + * The upper bound of the support is always positive infinity no matter * the parameters. * * @return upper bound of the support (always Double.POSITIVE_INFINITY) @@ -249,7 +249,7 @@ public class CauchyDistributionImpl extends AbstractContinuousDistribution /** * {@inheritDoc} - * + * * The mean is always undefined no matter the parameters. * * @return mean (always Double.NaN) @@ -261,7 +261,7 @@ public class CauchyDistributionImpl extends AbstractContinuousDistribution /** * {@inheritDoc} - * + * * The variance is always undefined no matter the parameters. * * @return variance (always Double.NaN) diff --git a/src/main/java/org/apache/commons/math/distribution/ChiSquaredDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/ChiSquaredDistributionImpl.java index 988841184..7c0f03c9c 100644 --- a/src/main/java/org/apache/commons/math/distribution/ChiSquaredDistributionImpl.java +++ b/src/main/java/org/apache/commons/math/distribution/ChiSquaredDistributionImpl.java @@ -196,8 +196,8 @@ public class ChiSquaredDistributionImpl /** * {@inheritDoc} - * - * The lower bound of the support is always 0 no matter the + * + * The lower bound of the support is always 0 no matter the * degrees of freedom. * * @return lower bound of the support (always 0) @@ -209,8 +209,8 @@ public class ChiSquaredDistributionImpl /** * {@inheritDoc} - * - * The upper bound of the support is always positive infinity no matter the + * + * The upper bound of the support is always positive infinity no matter the * degrees of freedom. * * @return upper bound of the support (always Double.POSITIVE_INFINITY) @@ -222,7 +222,7 @@ public class ChiSquaredDistributionImpl /** * {@inheritDoc} - * + * * For k degrees of freedom, the mean is * k * @@ -235,7 +235,7 @@ public class ChiSquaredDistributionImpl /** * {@inheritDoc} - * + * * For k degrees of freedom, the variance is * 2 * k * diff --git a/src/main/java/org/apache/commons/math/distribution/Distribution.java b/src/main/java/org/apache/commons/math/distribution/Distribution.java index 3edc3a4d2..2b58d8588 100644 --- a/src/main/java/org/apache/commons/math/distribution/Distribution.java +++ b/src/main/java/org/apache/commons/math/distribution/Distribution.java @@ -52,55 +52,55 @@ public interface Distribution { * @throws IllegalArgumentException if x0 > x1 */ double cumulativeProbability(double x0, double x1) throws MathException; - + /** - * Use this method to get the numerical value of the mean of this + * Use this method to get the numerical value of the mean of this * distribution. * * @return the mean or Double.NaN if it's not defined */ double getNumericalMean(); - + /** - * Use this method to get the numerical value of the variance of this + * Use this method to get the numerical value of the variance of this * distribution. * - * @return the variance (possibly Double.POSITIVE_INFINITY as - * for certain cases in {@link TDistributionImpl}) or + * @return the variance (possibly Double.POSITIVE_INFINITY as + * for certain cases in {@link TDistributionImpl}) or * Double.NaN if it's not defined */ - double getNumericalVariance(); - + double getNumericalVariance(); + /** - * Use this method to get information about whether the lower bound + * Use this method to get information about whether the lower bound * of the support is inclusive or not. * * @return whether the lower bound of the support is inclusive or not */ boolean isSupportLowerBoundInclusive(); - + /** - * Use this method to get information about whether the upper bound + * Use this method to get information about whether the upper bound * of the support is inclusive or not. * * @return whether the upper bound of the support is inclusive or not */ - boolean isSupportUpperBoundInclusive(); - + boolean isSupportUpperBoundInclusive(); + /** - * Use this method to get information about whether the support is connected, + * Use this method to get information about whether the support is connected, * i.e. whether all values between the lower and upper bound of the support * is included in the support. - * + * * For {@link AbstractIntegerDistribution} the support is discrete, so - * if this is true, then the support is + * if this is true, then the support is * {lower bound, lower bound + 1, ..., upper bound}. - * + * * For {@link AbstractContinuousDistribution} the support is continuous, so * if this is true, then the support is the interval * [lower bound, upper bound] - * where the limits are inclusive or not according to - * {@link #isSupportLowerBoundInclusive()} and {@link #isSupportUpperBoundInclusive()} + * where the limits are inclusive or not according to + * {@link #isSupportLowerBoundInclusive()} and {@link #isSupportUpperBoundInclusive()} * (in the example both are true). If both are false, then the support is the interval * (lower bound, upper bound) * diff --git a/src/main/java/org/apache/commons/math/distribution/ExponentialDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/ExponentialDistributionImpl.java index ae11154c3..5ed54648c 100644 --- a/src/main/java/org/apache/commons/math/distribution/ExponentialDistributionImpl.java +++ b/src/main/java/org/apache/commons/math/distribution/ExponentialDistributionImpl.java @@ -225,7 +225,7 @@ public class ExponentialDistributionImpl extends AbstractContinuousDistribution /** * {@inheritDoc} - * + * * The lower bound of the support is always 0 no matter the mean parameter. * * @return lower bound of the support (always 0) @@ -237,8 +237,8 @@ public class ExponentialDistributionImpl extends AbstractContinuousDistribution /** * {@inheritDoc} - * - * The upper bound of the support is always positive infinity + * + * The upper bound of the support is always positive infinity * no matter the mean parameter. * * @return upper bound of the support (always Double.POSITIVE_INFINITY) @@ -250,7 +250,7 @@ public class ExponentialDistributionImpl extends AbstractContinuousDistribution /** * {@inheritDoc} - * + * * For mean parameter k, the mean is * k * @@ -263,7 +263,7 @@ public class ExponentialDistributionImpl extends AbstractContinuousDistribution /** * {@inheritDoc} - * + * * For mean parameter k, the variance is * k^2 * diff --git a/src/main/java/org/apache/commons/math/distribution/FDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/FDistributionImpl.java index af9cfe8ae..ae7dc1063 100644 --- a/src/main/java/org/apache/commons/math/distribution/FDistributionImpl.java +++ b/src/main/java/org/apache/commons/math/distribution/FDistributionImpl.java @@ -235,10 +235,10 @@ public class FDistributionImpl protected double getSolverAbsoluteAccuracy() { return solverAbsoluteAccuracy; } - + /** * {@inheritDoc} - * + * * The lower bound of the support is always 0 no matter the parameters. * * @return lower bound of the support (always 0) @@ -250,8 +250,8 @@ public class FDistributionImpl /** * {@inheritDoc} - * - * The upper bound of the support is always positive infinity + * + * The upper bound of the support is always positive infinity * no matter the parameters. * * @return upper bound of the support (always Double.POSITIVE_INFINITY) @@ -263,8 +263,8 @@ public class FDistributionImpl /** * {@inheritDoc} - * - * For denominator degrees of freedom parameter b, + * + * For denominator degrees of freedom parameter b, * the mean is * * * @return {@inheritDoc} - */ + */ @Override - protected double calculateNumericalMean() { + protected double calculateNumericalMean() { final double denominatorDF = getDenominatorDegreesOfFreedom(); if (denominatorDF > 2) { - return denominatorDF / (denominatorDF - 2); + return denominatorDF / (denominatorDF - 2); } - + return Double.NaN; } /** * {@inheritDoc} - * - * For numerator degrees of freedom parameter a - * and denominator degrees of freedom parameter b, + * + * For numerator degrees of freedom parameter a + * and denominator degrees of freedom parameter b, * the variance is * *

- * + * * @param x * the first sample * @param y @@ -86,7 +86,7 @@ public interface WilcoxonSignedRankTest { * meaningful. * *

- * + * * @param x * the first sample * @param y diff --git a/src/main/java/org/apache/commons/math/stat/inference/WilcoxonSignedRankTestImpl.java b/src/main/java/org/apache/commons/math/stat/inference/WilcoxonSignedRankTestImpl.java index 82dc7faa3..5d94c6164 100644 --- a/src/main/java/org/apache/commons/math/stat/inference/WilcoxonSignedRankTestImpl.java +++ b/src/main/java/org/apache/commons/math/stat/inference/WilcoxonSignedRankTestImpl.java @@ -25,7 +25,7 @@ import org.apache.commons.math.util.FastMath; /** * An implementation of the Wilcoxon signed-rank test. - * + * * @version $Revision$ $Date$ */ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { @@ -44,7 +44,7 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { /** * Create a test instance using the given strategies for NaN's and ties. * Only use this if you are sure of what you are doing. - * + * * @param nanStrategy * specifies the strategy that should be used for Double.NaN's * @param tiesStrategy @@ -57,7 +57,7 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { /** * Ensures that the provided arrays fulfills the assumptions. - * + * * @param x * @param y * @throws IllegalArgumentException @@ -86,7 +86,7 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { /** * Calculates y[i] - x[i] for all i - * + * * @param x * @param y * @throws IllegalArgumentException @@ -106,7 +106,7 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { /** * Calculates |z[i]| for all i - * + * * @param z * @throws IllegalArgumentException * if assumptions are not met @@ -133,7 +133,7 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { /** * {@inheritDoc} - * + * * @param x * the first sample * @param y @@ -144,7 +144,7 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { */ public double wilcoxonSignedRank(final double[] x, final double[] y) throws IllegalArgumentException { - + ensureDataConformance(x, y); // throws IllegalArgumentException if x and y are not correctly @@ -171,12 +171,12 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { /** * Algorithm inspired by * http://www.fon.hum.uva.nl/Service/Statistics/Signed_Rank_Algorihms.html#C - * by Rob van Son, Institute of Phonetic Sciences & IFOTT, + * by Rob van Son, Institute of Phonetic Sciences & IFOTT, * University of Amsterdam - * + * * @param Wmax largest Wilcoxon signed rank value * @param N number of subjects (corresponding to x.length) - * @return two-sided exact p-value + * @return two-sided exact p-value */ private double calculateExactPValue(final double Wmax, final int N) { @@ -208,22 +208,22 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { */ return 2 * ((double) largerRankSums) / ((double) m); } - + /** * @param Wmin smallest Wilcoxon signed rank value * @param N number of subjects (corresponding to x.length) - * @return two-sided asymptotic p-value + * @return two-sided asymptotic p-value * @throws MathException if an error occurs computing the p-value */ private double calculateAsymptoticPValue(final double Wmin, final int N) throws MathException { - + final double ES = (double) (N * (N + 1)) / 4.0; - - /* Same as (but saves computations): + + /* Same as (but saves computations): * final double VarW = ((double) (N * (N + 1) * (2*N + 1))) / 24; */ final double VarS = ES * ((double) (2 * N + 1) / 6.0); - + // - 0.5 is a continuity correction final double z = (Wmin - ES - 0.5) / FastMath.sqrt(VarS); @@ -234,7 +234,7 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { /** * {@inheritDoc} - * + * * @param x * the first sample * @param y @@ -251,16 +251,16 @@ public class WilcoxonSignedRankTestImpl implements WilcoxonSignedRankTest { public double wilcoxonSignedRankTest(final double[] x, final double[] y, boolean exactPValue) throws IllegalArgumentException, MathException { - + ensureDataConformance(x, y); final int N = x.length; final double Wmax = wilcoxonSignedRank(x, y); - + if (exactPValue && N > 30) { throw new IllegalArgumentException("Exact test can only be made for N <= 30."); } - + if (exactPValue) { return calculateExactPValue(Wmax, N); } else { diff --git a/src/main/java/org/apache/commons/math/util/ResizableDoubleArray.java b/src/main/java/org/apache/commons/math/util/ResizableDoubleArray.java index d03e941cc..d994a4278 100644 --- a/src/main/java/org/apache/commons/math/util/ResizableDoubleArray.java +++ b/src/main/java/org/apache/commons/math/util/ResizableDoubleArray.java @@ -187,7 +187,7 @@ public class ResizableDoubleArray implements DoubleArray, Serializable { numElements = initialArray.length; } } - + /** *

* Create a ResizableArray with the specified initial capacity @@ -302,7 +302,7 @@ public class ResizableDoubleArray implements DoubleArray, Serializable { contract(); } } - + /** * Adds several element to the end of this expandable array. *