http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/gradient/NonLinearConjugateGradientOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/gradient/NonLinearConjugateGradientOptimizer.java b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/gradient/NonLinearConjugateGradientOptimizer.java index 75dd024..2bd188e 100644 --- a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/gradient/NonLinearConjugateGradientOptimizer.java +++ b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/gradient/NonLinearConjugateGradientOptimizer.java @@ -31,11 +31,11 @@ import org.apache.commons.math4.optim.nonlinear.scalar.LineSearch; /** * Non-linear conjugate gradient optimizer. - * <br/> + * <br> * This class supports both the Fletcher-Reeves and the Polak-Ribière * update formulas for the conjugate search directions. * It also supports optional preconditioning. - * <br/> + * <br> * Constraints are not supported: the call to * {@link #optimize(OptimizationData[]) optimize} will throw * {@link MathUnsupportedOperationException} if bounds are passed to it.
http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/AbstractSimplex.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/AbstractSimplex.java b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/AbstractSimplex.java index 45da036..4ddfaed 100644 --- a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/AbstractSimplex.java +++ b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/AbstractSimplex.java @@ -34,12 +34,12 @@ import org.apache.commons.math4.optim.PointValuePair; /** * This class implements the simplex concept. * It is intended to be used in conjunction with {@link SimplexOptimizer}. - * <br/> + * <br> * The initial configuration of the simplex is set by the constructors * {@link #AbstractSimplex(double[])} or {@link #AbstractSimplex(double[][])}. * The other {@link #AbstractSimplex(int) constructor} will set all steps * to 1, thus building a default configuration from a unit hypercube. - * <br/> + * <br> * Users <em>must</em> call the {@link #build(double[]) build} method in order * to create the data structure that will be acted on by the other methods of * this class. http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/BOBYQAOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/BOBYQAOptimizer.java b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/BOBYQAOptimizer.java index 74bf89d..4366b15 100644 --- a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/BOBYQAOptimizer.java +++ b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/BOBYQAOptimizer.java @@ -35,7 +35,7 @@ import org.apache.commons.math4.util.FastMath; * <a href="http://plato.asu.edu/ftp/other_software/bobyqa.zip";>here</a>. * See <a href="http://www.optimization-online.org/DB_HTML/2010/05/2616.html";> * this paper</a> for an introduction. - * <br/> + * <br> * BOBYQA is particularly well suited for high dimensional problems * where derivatives are not available. In most cases it outperforms the * {@link PowellOptimizer} significantly. Stochastic algorithms like @@ -148,9 +148,9 @@ public class BOBYQAOptimizer /** * Differences {@link #getLowerBound()} - {@link #originShift}. * All the components of every {@link #trustRegionCenterOffset} are going - * to satisfy the bounds<br/> + * to satisfy the bounds<br> * {@link #getLowerBound() lowerBound}<sub>i</sub> ≤ - * {@link #trustRegionCenterOffset}<sub>i</sub>,<br/> + * {@link #trustRegionCenterOffset}<sub>i</sub>,<br> * with appropriate equalities when {@link #trustRegionCenterOffset} is * on a constraint boundary. * XXX "sl" in the original code. @@ -159,9 +159,9 @@ public class BOBYQAOptimizer /** * Differences {@link #getUpperBound()} - {@link #originShift} * All the components of every {@link #trustRegionCenterOffset} are going - * to satisfy the bounds<br/> + * to satisfy the bounds<br> * {@link #trustRegionCenterOffset}<sub>i</sub> ≤ - * {@link #getUpperBound() upperBound}<sub>i</sub>,<br/> + * {@link #getUpperBound() upperBound}<sub>i</sub>,<br> * with appropriate equalities when {@link #trustRegionCenterOffset} is * on a constraint boundary. * XXX "su" in the original code. http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/CMAESOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/CMAESOptimizer.java b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/CMAESOptimizer.java index e47266a..18af3c0 100644 --- a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/CMAESOptimizer.java +++ b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/CMAESOptimizer.java @@ -56,16 +56,16 @@ import org.apache.commons.math4.util.MathArrays; * <p> * In general, on smooth objective functions the CMA-ES is roughly ten times * slower than BFGS (counting objective function evaluations, no gradients provided). - * For up to <math>N=10</math> variables also the derivative-free simplex + * For up to <code>N=10</code> variables also the derivative-free simplex * direct search method (Nelder and Mead) can be faster, but it is * far less reliable than CMA-ES. * <p> * The CMA-ES is particularly well suited for non-separable * and/or badly conditioned problems. To observe the advantage of CMA compared * to a conventional evolution strategy, it will usually take about - * <math>30 N</math> function evaluations. On difficult problems the complete + * <code>30 N</code> function evaluations. On difficult problems the complete * optimization (a single run) is expected to take <em>roughly</em> between - * <math>30 N</math> and <math>300 N<sup>2</sup></math> + * <code>30 N</code> and <code>300 N<sup>2</sup></code> * function evaluations. * <p> * This implementation is translated and adapted from the Matlab version http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/PowellOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/PowellOptimizer.java b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/PowellOptimizer.java index 90d81de..f4d5fed 100644 --- a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/PowellOptimizer.java +++ b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/PowellOptimizer.java @@ -34,14 +34,14 @@ import org.apache.commons.math4.util.MathArrays; * This code is translated and adapted from the Python version of this * algorithm (as implemented in module {@code optimize.py} v0.5 of * <em>SciPy</em>). - * <br/> + * <br> * The default stopping criterion is based on the differences of the * function value between two successive iterations. It is however possible * to define a custom convergence checker that might terminate the algorithm * earlier. - * <br/> + * <br> * Line search is performed by the {@link LineSearch} class. - * <br/> + * <br> * Constraints are not supported: the call to * {@link #optimize(OptimizationData[]) optimize} will throw * {@link MathUnsupportedOperationException} if bounds are passed to it. @@ -77,7 +77,7 @@ public class PowellOptimizer * This constructor allows to specify a user-defined convergence checker, * in addition to the parameters that control the default convergence * checking procedure. - * <br/> + * <br> * The internal line search tolerances are set to the square-root of their * corresponding value in the multivariate optimizer. * @@ -131,7 +131,7 @@ public class PowellOptimizer /** * The parameters control the default convergence checking procedure. - * <br/> + * <br> * The internal line search tolerances are set to the square-root of their * corresponding value in the multivariate optimizer. * http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/SimplexOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/SimplexOptimizer.java b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/SimplexOptimizer.java index 9658944..54e2884 100644 --- a/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/SimplexOptimizer.java +++ b/src/main/java/org/apache/commons/math4/optim/nonlinear/scalar/noderiv/SimplexOptimizer.java @@ -50,7 +50,7 @@ import org.apache.commons.math4.optim.nonlinear.scalar.MultivariateOptimizer; * the objective function values at the vertices of a simplex (which is a * set of n+1 points in dimension n) that is updated by the algorithms * steps. - * <p> + * </p> * <p> * The simplex update procedure ({@link NelderMeadSimplex} or * {@link MultiDirectionalSimplex}) must be passed to the @@ -79,7 +79,7 @@ import org.apache.commons.math4.optim.nonlinear.scalar.MultivariateOptimizer; * MultivariateFunctionMappingAdapter} or * {@link org.apache.commons.math4.optim.nonlinear.scalar.MultivariateFunctionPenaltyAdapter * MultivariateFunctionPenaltyAdapter}. - * <br/> + * <br> * The call to {@link #optimize(OptimizationData[]) optimize} will throw * {@link MathUnsupportedOperationException} if bounds are passed to it. * </p> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/package-info.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/package-info.java b/src/main/java/org/apache/commons/math4/optim/package-info.java index 8f3d99c..d6b6348 100644 --- a/src/main/java/org/apache/commons/math4/optim/package-info.java +++ b/src/main/java/org/apache/commons/math4/optim/package-info.java @@ -23,7 +23,7 @@ * a scalar function, called the * {@link org.apache.commons.math4.optim.nonlinear.scalar.ObjectiveFunction <em>objective * function</em>}. - * <br/> + * <br> * For some scalar objective functions the gradient can be computed (analytically * or numerically). Algorithms that use this knowledge are defined in the * {@link org.apache.commons.math4.optim.nonlinear.scalar.gradient} package. http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/univariate/BrentOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/univariate/BrentOptimizer.java b/src/main/java/org/apache/commons/math4/optim/univariate/BrentOptimizer.java index e1b2d9d..6cc67b8 100644 --- a/src/main/java/org/apache/commons/math4/optim/univariate/BrentOptimizer.java +++ b/src/main/java/org/apache/commons/math4/optim/univariate/BrentOptimizer.java @@ -30,7 +30,7 @@ import org.apache.commons.numbers.core.Precision; * It implements Richard Brent's algorithm (from his book "Algorithms for * Minimization without Derivatives", p. 79) for finding minima of real * univariate functions. - * <br/> + * <br> * This code is an adaptation, partly based on the Python code from SciPy * (module "optimize.py" v0.5); the original algorithm is also modified * <ul> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/univariate/MultiStartUnivariateOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/univariate/MultiStartUnivariateOptimizer.java b/src/main/java/org/apache/commons/math4/optim/univariate/MultiStartUnivariateOptimizer.java index 373a307..6b3e9af 100644 --- a/src/main/java/org/apache/commons/math4/optim/univariate/MultiStartUnivariateOptimizer.java +++ b/src/main/java/org/apache/commons/math4/optim/univariate/MultiStartUnivariateOptimizer.java @@ -31,7 +31,7 @@ import org.apache.commons.rng.UniformRandomProvider; /** * Special implementation of the {@link UnivariateOptimizer} interface * adding multi-start features to an existing optimizer. - * <br/> + * <br> * This class wraps an optimizer in order to use it several times in * turn with different starting points (trying to avoid being trapped * in a local extremum when looking for a global one). @@ -99,7 +99,7 @@ public class MultiStartUnivariateOptimizer * restarts. The {@code optimize} method returns the best point only. * This method returns all the points found at the end of each starts, * including the best one already returned by the {@code optimize} method. - * <br/> + * <br> * The returned array as one element for each start as specified * in the constructor. It is ordered with the results from the * runs that did converge first, sorted from best to worst http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/univariate/SearchInterval.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/univariate/SearchInterval.java b/src/main/java/org/apache/commons/math4/optim/univariate/SearchInterval.java index 172cf80..8bed386 100644 --- a/src/main/java/org/apache/commons/math4/optim/univariate/SearchInterval.java +++ b/src/main/java/org/apache/commons/math4/optim/univariate/SearchInterval.java @@ -22,7 +22,7 @@ import org.apache.commons.math4.optim.OptimizationData; /** * Search interval and (optional) start value. - * <br/> + * <br> * Immutable class. * * @since 3.1 http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/optim/univariate/SimpleUnivariateValueChecker.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optim/univariate/SimpleUnivariateValueChecker.java b/src/main/java/org/apache/commons/math4/optim/univariate/SimpleUnivariateValueChecker.java index b37a5b3..878dd61 100644 --- a/src/main/java/org/apache/commons/math4/optim/univariate/SimpleUnivariateValueChecker.java +++ b/src/main/java/org/apache/commons/math4/optim/univariate/SimpleUnivariateValueChecker.java @@ -29,7 +29,7 @@ import org.apache.commons.math4.util.FastMath; * difference between the objective function values is smaller than a * threshold or if either the absolute difference between the objective * function values is smaller than another threshold. - * <br/> + * <br> * The {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair) * converged} method will also return {@code true} if the number of iterations * has been set (see {@link #SimpleUnivariateValueChecker(double,double,int) http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/random/RngAdaptor.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/random/RngAdaptor.java b/src/main/java/org/apache/commons/math4/random/RngAdaptor.java index 2852d58..7e91357 100644 --- a/src/main/java/org/apache/commons/math4/random/RngAdaptor.java +++ b/src/main/java/org/apache/commons/math4/random/RngAdaptor.java @@ -63,7 +63,7 @@ import org.apache.commons.rng.core.RandomProviderDefaultState; * new API} as it defines a "post-processing" of the output of a * <i>uniform</i> RNG in order to follow a different distribution. * </li> - * </p> + * </ul> * * @since 4.0 * http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/special/BesselJ.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/special/BesselJ.java b/src/main/java/org/apache/commons/math4/special/BesselJ.java index ff82161..b677939 100644 --- a/src/main/java/org/apache/commons/math4/special/BesselJ.java +++ b/src/main/java/org/apache/commons/math4/special/BesselJ.java @@ -50,7 +50,7 @@ import org.apache.commons.math4.util.MathArrays; * D. J., Math. Comp. 26, 1972, pp 941-947.</li> * <li>"Bessel Functions of Real Argument and Integer Order," Sookne, D. J., NBS * Jour. of Res. B. 77B, 1973, pp 125-132.</li> - * </ul> </p> + * </ul> * @since 3.4 */ public class BesselJ @@ -176,8 +176,7 @@ public class BesselJ * {@link #getVals()} returns the computed function values. * {@link #getnVals()} is the number of values among those returned by {@link #getnVals()} * that can be considered accurate. - * </p><p> - * <ul> + * </p><ul> * <li>nVals < 0: An argument is out of range. For example, nb <= 0, alpha * < 0 or > 1, or x is too large. In this case, b(0) is set to zero, the * remainder of the b-vector is not calculated, and nVals is set to @@ -188,7 +187,7 @@ public class BesselJ * precision is lost for nVals < n <= nb. If b(n) does not vanish for n > * nVals (because it is too small to be represented), and b(n)/b(nVals) = * \(10^{-k}\), then only the first NSIG-k significant figures of b(n) can be - * trusted.</li></ul></p> + * trusted.</li></ul> */ public static class BesselJResult { http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/special/Erf.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/special/Erf.java b/src/main/java/org/apache/commons/math4/special/Erf.java index 9872230..c0c4ce0 100644 --- a/src/main/java/org/apache/commons/math4/special/Erf.java +++ b/src/main/java/org/apache/commons/math4/special/Erf.java @@ -29,10 +29,10 @@ public class Erf { * The number {@code X_CRIT} is used by {@link #erf(double, double)} internally. * This number solves {@code erf(x)=0.5} within 1ulp. * More precisely, the current implementations of - * {@link #erf(double)} and {@link #erfc(double)} satisfy:<br/> - * {@code erf(X_CRIT) < 0.5},<br/> - * {@code erf(Math.nextUp(X_CRIT) > 0.5},<br/> - * {@code erfc(X_CRIT) = 0.5}, and<br/> + * {@link #erf(double)} and {@link #erfc(double)} satisfy:<br> + * {@code erf(X_CRIT) < 0.5},<br> + * {@code erf(Math.nextUp(X_CRIT) > 0.5},<br> + * {@code erfc(X_CRIT) = 0.5}, and<br> * {@code erfc(Math.nextUp(X_CRIT) < 0.5} */ private static final double X_CRIT = 0.4769362762044697; @@ -74,7 +74,7 @@ public class Erf { * Returns the complementary error function. * * <p>erfc(x) = 2/√π <sub>x</sub>∫<sup>∞</sup> e<sup>-t<sup>2</sup></sup>dt - * <br/> + * <br> * = 1 - {@link #erf(double) erf(x)} </p> * * <p>This implementation computes erfc(x) using the http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/Frequency.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/Frequency.java b/src/main/java/org/apache/commons/math4/stat/Frequency.java index f676720..dfcca5a 100644 --- a/src/main/java/org/apache/commons/math4/stat/Frequency.java +++ b/src/main/java/org/apache/commons/math4/stat/Frequency.java @@ -56,7 +56,7 @@ import org.apache.commons.math4.util.MathUtils; * Since they are not Comparable with each other the user must do any necessary coercion. * Float.NaN and Double.NaN are not treated specially; they may occur in input and will * occur in output if appropriate. - * </b> + * </p> * <p> * The values are ordered using the default (natural order), unless a * <code>Comparator</code> is supplied in the constructor.</p> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/StatUtils.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/StatUtils.java b/src/main/java/org/apache/commons/math4/stat/StatUtils.java index a6813ce..d267bce 100644 --- a/src/main/java/org/apache/commons/math4/stat/StatUtils.java +++ b/src/main/java/org/apache/commons/math4/stat/StatUtils.java @@ -520,7 +520,6 @@ public final class StatUtils { * <code>Double.NaN</code> if the array is empty. * <p> * Throws <code>MathIllegalArgumentException</code> if the array is null. - * <p> * <ul> * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> @@ -542,7 +541,6 @@ public final class StatUtils { * <p> * Throws <code>MathIllegalArgumentException</code> if the array is null or * the array index parameters are not valid. - * <p> * <ul> * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> @@ -567,7 +565,6 @@ public final class StatUtils { * <code>Double.NaN</code> if the array is empty. * <p> * Throws <code>MathIllegalArgumentException</code> if the array is null. - * <p> * <ul> * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> @@ -589,7 +586,6 @@ public final class StatUtils { * <p> * Throws <code>MathIllegalArgumentException</code> if the array is null or * the array index parameters are not valid. - * <p> * <ul> * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> @@ -612,7 +608,6 @@ public final class StatUtils { /** * Returns an estimate of the <code>p</code>th percentile of the values * in the <code>values</code> array. - * <p> * <ul> * <li>Returns <code>Double.NaN</code> if <code>values</code> has length * <code>0</code></li> @@ -640,7 +635,6 @@ public final class StatUtils { * in the <code>values</code> array, starting with the element in (0-based) * position <code>begin</code> in the array and including <code>length</code> * values. - * <p> * <ul> * <li>Returns <code>Double.NaN</code> if <code>length = 0</code></li> * <li>Returns (for any value of <code>p</code>) <code>values[begin]</code> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/correlation/KendallsCorrelation.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/correlation/KendallsCorrelation.java b/src/main/java/org/apache/commons/math4/stat/correlation/KendallsCorrelation.java index 32ed6d0..1fdb155 100644 --- a/src/main/java/org/apache/commons/math4/stat/correlation/KendallsCorrelation.java +++ b/src/main/java/org/apache/commons/math4/stat/correlation/KendallsCorrelation.java @@ -27,7 +27,7 @@ import org.apache.commons.math4.util.FastMath; import org.apache.commons.math4.util.Pair; /** - * Implementation of Kendall's Tau-b rank correlation</a>. + * Implementation of Kendall's Tau-b rank correlation. * <p> * A pair of observations (x<sub>1</sub>, y<sub>1</sub>) and * (x<sub>2</sub>, y<sub>2</sub>) are considered <i>concordant</i> if @@ -40,9 +40,9 @@ import org.apache.commons.math4.util.Pair; * discordant. * <p> * Kendall's Tau-b is defined as: - * <pre> + * <div style="white-space: pre"><code> * tau<sub>b</sub> = (n<sub>c</sub> - n<sub>d</sub>) / sqrt((n<sub>0</sub> - n<sub>1</sub>) * (n<sub>0</sub> - n<sub>2</sub>)) - * </pre> + * </code></div> * <p> * where: * <ul> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/correlation/PearsonsCorrelation.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/correlation/PearsonsCorrelation.java b/src/main/java/org/apache/commons/math4/stat/correlation/PearsonsCorrelation.java index 6059752..b14f8a6 100644 --- a/src/main/java/org/apache/commons/math4/stat/correlation/PearsonsCorrelation.java +++ b/src/main/java/org/apache/commons/math4/stat/correlation/PearsonsCorrelation.java @@ -144,11 +144,11 @@ public class PearsonsCorrelation { /** * Returns a matrix of standard errors associated with the estimates - * in the correlation matrix.<br/> + * in the correlation matrix.<br> * <code>getCorrelationStandardErrors().getEntry(i,j)</code> is the standard * error associated with <code>getCorrelationMatrix.getEntry(i,j)</code> * - * <p>The formula used to compute the standard error is <br/> + * <p>The formula used to compute the standard error is <br> * <code>SE<sub>r</sub> = ((1 - r<sup>2</sup>) / (n - 2))<sup>1/2</sup></code> * where <code>r</code> is the estimated correlation coefficient and * <code>n</code> is the number of observations in the source dataset.</p> @@ -288,9 +288,9 @@ public class PearsonsCorrelation { /** * Derives a correlation matrix from a covariance matrix. * - * <p>Uses the formula <br/> + * <p>Uses the formula <br> * <code>r(X,Y) = cov(X,Y)/s(X)s(Y)</code> where - * <code>r(·,·)</code> is the correlation coefficient and + * <code>r(·,·)</code> is the correlation coefficient and * <code>s(·)</code> means standard deviation.</p> * * @param covarianceMatrix the covariance matrix http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/DescriptiveStatistics.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/DescriptiveStatistics.java b/src/main/java/org/apache/commons/math4/stat/descriptive/DescriptiveStatistics.java index 99e02cc..8ae7d7a 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/DescriptiveStatistics.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/DescriptiveStatistics.java @@ -435,7 +435,7 @@ public class DescriptiveStatistics implements StatisticalSummary, Serializable { * <code>MathIllegalArgumentException</code> is thrown)</li> * <li>at least one value must be stored (returns <code>Double.NaN * </code> otherwise)</li> - * </ul></p> + * </ul> * * @param p the requested percentile (scaled from 0 - 100) * @return An estimate for the pth percentile of the stored data http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/MultivariateSummaryStatistics.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/MultivariateSummaryStatistics.java b/src/main/java/org/apache/commons/math4/stat/descriptive/MultivariateSummaryStatistics.java index a161fc8..5248b5c 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/MultivariateSummaryStatistics.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/MultivariateSummaryStatistics.java @@ -453,7 +453,7 @@ public class MultivariateSummaryStatistics * @throws DimensionMismatchException if the array dimension * does not match the one used at construction * @throws MathIllegalStateException if data has already been added - * (i.e if n > 0) + * (i.e if n > 0) */ public void setSumImpl(StorelessUnivariateStatistic[] sumImpl) throws MathIllegalStateException, DimensionMismatchException { @@ -480,7 +480,7 @@ public class MultivariateSummaryStatistics * @throws DimensionMismatchException if the array dimension * does not match the one used at construction * @throws MathIllegalStateException if data has already been added - * (i.e if n > 0) + * (i.e if n > 0) */ public void setSumsqImpl(StorelessUnivariateStatistic[] sumsqImpl) throws MathIllegalStateException, DimensionMismatchException { @@ -507,7 +507,7 @@ public class MultivariateSummaryStatistics * @throws DimensionMismatchException if the array dimension * does not match the one used at construction * @throws MathIllegalStateException if data has already been added - * (i.e if n > 0) + * (i.e if n > 0) */ public void setMinImpl(StorelessUnivariateStatistic[] minImpl) throws MathIllegalStateException, DimensionMismatchException { @@ -534,7 +534,7 @@ public class MultivariateSummaryStatistics * @throws DimensionMismatchException if the array dimension * does not match the one used at construction * @throws MathIllegalStateException if data has already been added - * (i.e if n > 0) + * (i.e if n > 0) */ public void setMaxImpl(StorelessUnivariateStatistic[] maxImpl) throws MathIllegalStateException, DimensionMismatchException{ @@ -561,7 +561,7 @@ public class MultivariateSummaryStatistics * @throws DimensionMismatchException if the array dimension * does not match the one used at construction * @throws MathIllegalStateException if data has already been added - * (i.e if n > 0) + * (i.e if n > 0) */ public void setSumLogImpl(StorelessUnivariateStatistic[] sumLogImpl) throws MathIllegalStateException, DimensionMismatchException{ @@ -588,7 +588,7 @@ public class MultivariateSummaryStatistics * @throws DimensionMismatchException if the array dimension * does not match the one used at construction * @throws MathIllegalStateException if data has already been added - * (i.e if n > 0) + * (i.e if n > 0) */ public void setGeoMeanImpl(StorelessUnivariateStatistic[] geoMeanImpl) throws MathIllegalStateException, DimensionMismatchException { @@ -615,7 +615,7 @@ public class MultivariateSummaryStatistics * @throws DimensionMismatchException if the array dimension * does not match the one used at construction * @throws MathIllegalStateException if data has already been added - * (i.e if n > 0) + * (i.e if n > 0) */ public void setMeanImpl(StorelessUnivariateStatistic[] meanImpl) throws MathIllegalStateException, DimensionMismatchException{ http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/SummaryStatistics.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/SummaryStatistics.java b/src/main/java/org/apache/commons/math4/stat/descriptive/SummaryStatistics.java index 91f77fb..9ab88c1 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/SummaryStatistics.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/SummaryStatistics.java @@ -446,7 +446,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable { * </p> * @param sumImpl the StorelessUnivariateStatistic instance to use for * computing the Sum - * @throws MathIllegalStateException if data has already been added (i.e if n >0) + * @throws MathIllegalStateException if data has already been added (i.e if n >0) * @since 1.2 */ public void setSumImpl(StorelessUnivariateStatistic sumImpl) @@ -476,7 +476,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable { * </p> * @param sumsqImpl the StorelessUnivariateStatistic instance to use for * computing the sum of squares - * @throws MathIllegalStateException if data has already been added (i.e if n > 0) + * @throws MathIllegalStateException if data has already been added (i.e if n > 0) * @since 1.2 */ public void setSumsqImpl(StorelessUnivariateStatistic sumsqImpl) @@ -506,7 +506,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable { * </p> * @param minImpl the StorelessUnivariateStatistic instance to use for * computing the minimum - * @throws MathIllegalStateException if data has already been added (i.e if n > 0) + * @throws MathIllegalStateException if data has already been added (i.e if n > 0) * @since 1.2 */ public void setMinImpl(StorelessUnivariateStatistic minImpl) @@ -536,7 +536,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable { * </p> * @param maxImpl the StorelessUnivariateStatistic instance to use for * computing the maximum - * @throws MathIllegalStateException if data has already been added (i.e if n > 0) + * @throws MathIllegalStateException if data has already been added (i.e if n > 0) * @since 1.2 */ public void setMaxImpl(StorelessUnivariateStatistic maxImpl) @@ -566,7 +566,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable { * </p> * @param sumLogImpl the StorelessUnivariateStatistic instance to use for * computing the log sum - * @throws MathIllegalStateException if data has already been added (i.e if n > 0) + * @throws MathIllegalStateException if data has already been added (i.e if n > 0) * @since 1.2 */ public void setSumLogImpl(StorelessUnivariateStatistic sumLogImpl) @@ -597,7 +597,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable { * </p> * @param geoMeanImpl the StorelessUnivariateStatistic instance to use for * computing the geometric mean - * @throws MathIllegalStateException if data has already been added (i.e if n > 0) + * @throws MathIllegalStateException if data has already been added (i.e if n > 0) * @since 1.2 */ public void setGeoMeanImpl(StorelessUnivariateStatistic geoMeanImpl) @@ -627,7 +627,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable { * </p> * @param meanImpl the StorelessUnivariateStatistic instance to use for * computing the mean - * @throws MathIllegalStateException if data has already been added (i.e if n > 0) + * @throws MathIllegalStateException if data has already been added (i.e if n > 0) * @since 1.2 */ public void setMeanImpl(StorelessUnivariateStatistic meanImpl) @@ -657,7 +657,7 @@ public class SummaryStatistics implements StatisticalSummary, Serializable { * </p> * @param varianceImpl the StorelessUnivariateStatistic instance to use for * computing the variance - * @throws MathIllegalStateException if data has already been added (i.e if n > 0) + * @throws MathIllegalStateException if data has already been added (i.e if n > 0) * @since 1.2 */ public void setVarianceImpl(StorelessUnivariateStatistic varianceImpl) http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/moment/FirstMoment.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/FirstMoment.java b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/FirstMoment.java index 50b107f..e02a7cb 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/FirstMoment.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/FirstMoment.java @@ -31,12 +31,11 @@ import org.apache.commons.math4.util.MathUtils; * <p> * To limit numeric errors, the value of the statistic is computed using the * following recursive updating algorithm: </p> - * <p> * <ol> * <li>Initialize <code>m = </code> the first value</li> * <li>For each additional value, update using <br> * <code>m = m + (new value - m) / (number of observations)</code></li> - * </ol></p> + * </ol> * <p> * Returns <code>Double.NaN</code> if the dataset is empty. Note that * Double.NaN may also be returned if the input includes NaN and / or infinite http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/moment/GeometricMean.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/GeometricMean.java b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/GeometricMean.java index 938930b..aaeffe6 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/GeometricMean.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/GeometricMean.java @@ -42,7 +42,7 @@ import org.apache.commons.math4.util.MathUtils; * <li>If both <code>Double.POSITIVE_INFINITY</code> and * <code>Double.NEGATIVE_INFINITY</code> are among the values, the result is * <code>NaN.</code></li> - * </ul> </p> + * </ul> * <p> * <strong>Note that this implementation is not synchronized.</strong> If * multiple threads access an instance of this class concurrently, and at least @@ -162,7 +162,7 @@ public class GeometricMean extends AbstractStorelessUnivariateStatistic implemen * @param sumLogImpl the StorelessUnivariateStatistic instance to use * for computing the log sum * @throws MathIllegalStateException if data has already been added - * (i.e if n > 0) + * (i.e if n > 0) */ public void setSumLogImpl(StorelessUnivariateStatistic sumLogImpl) throws MathIllegalStateException { http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Mean.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Mean.java b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Mean.java index 4a23b0e..2503039 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Mean.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Mean.java @@ -199,7 +199,7 @@ public class Mean extends AbstractStorelessUnivariateStatistic * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> * <li>the start and length arguments do not determine a valid array</li> - * </ul></p> + * </ul> * * @param values the input array * @param weights the weights array @@ -245,7 +245,7 @@ public class Mean extends AbstractStorelessUnivariateStatistic * <li>the weights array contains one or more infinite values</li> * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> - * </ul></p> + * </ul> * * @param values the input array * @param weights the weights array http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SecondMoment.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SecondMoment.java b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SecondMoment.java index 6cab875..878ebe4 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SecondMoment.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SecondMoment.java @@ -31,7 +31,7 @@ import org.apache.commons.math4.util.MathUtils; * <li> dev = (current obs - previous mean) </li> * <li> n = number of observations (including current obs) </li> * </ul> - * Then</p> + * Then * <p> * new value = old value + dev^2 * (n -1) / n.</p> * <p> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SemiVariance.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SemiVariance.java b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SemiVariance.java index 2c8f840..b1427b8 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SemiVariance.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/SemiVariance.java @@ -28,8 +28,8 @@ import org.apache.commons.math4.util.MathUtils; /** * <p>Computes the semivariance of a set of values with respect to a given cutoff value. * We define the <i>downside semivariance</i> of a set of values <code>x</code> - * against the <i>cutoff value</i> <code>cutoff</code> to be <br/> - * <code>Σ (x[i] - target)<sup>2</sup> / df</code> <br/> + * against the <i>cutoff value</i> <code>cutoff</code> to be <br> + * <code>Σ (x[i] - target)<sup>2</sup> / df</code> <br> * where the sum is taken over all <code>i</code> such that <code>x[i] < cutoff</code> * and <code>df</code> is the length of <code>x</code> (non-bias-corrected) or * one less than this number (bias corrected). The <i>upside semivariance</i> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Variance.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Variance.java b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Variance.java index d88f952..7ed06bc 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Variance.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/moment/Variance.java @@ -52,7 +52,7 @@ import org.apache.commons.math4.util.MathUtils; * <code>incrementAll</code> and then executing <code>getResult</code> will * sometimes give a different, less accurate, result than executing * <code>evaluate</code> with the full array of values. The former approach - * should only be used when the full array of values is not available.</p> + * should only be used when the full array of values is not available. * <p> * The "population variance" ( sum((x_i - mean)^2) / n ) can also * be computed using this statistic. The <code>isBiasCorrected</code> @@ -299,7 +299,7 @@ public class Variance extends AbstractStorelessUnivariateStatistic implements Se * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> * <li>the start and length arguments do not determine a valid array</li> - * </ul></p> + * </ul> * <p> * Does not change the internal state of the statistic.</p> * <p> @@ -335,10 +335,10 @@ public class Variance extends AbstractStorelessUnivariateStatistic implements Se * <p> * Returns the weighted variance of the entries in the the input array.</p> * <p> - * Uses the formula <pre> + * Uses the formula <div style="white-space:pre"><code> * Σ(weights[i]*(values[i] - weightedMean)<sup>2</sup>)/(Σ(weights[i]) - 1) - * </pre> - * where weightedMean is the weighted mean</p> + * </code></div> + * where weightedMean is the weighted mean * <p> * This formula will not return the same result as the unweighted variance when all * weights are equal, unless all weights are equal to 1. The formula assumes that @@ -357,7 +357,7 @@ public class Variance extends AbstractStorelessUnivariateStatistic implements Se * <li>the weights array contains one or more infinite values</li> * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> - * </ul></p> + * </ul> * <p> * Does not change the internal state of the statistic.</p> * <p> @@ -463,9 +463,9 @@ public class Variance extends AbstractStorelessUnivariateStatistic implements Se * the input array, using the precomputed weighted mean value. Returns * <code>Double.NaN</code> if the designated subarray is empty. * <p> - * Uses the formula <pre> + * Uses the formula <div style="white-space:pre"><code> * Σ(weights[i]*(values[i] - mean)<sup>2</sup>)/(Σ(weights[i]) - 1) - * </pre></p> + * </code></div> * <p> * The formula used assumes that the supplied mean value is the weighted arithmetic * mean of the sample data, not a known population parameter. This method @@ -490,7 +490,7 @@ public class Variance extends AbstractStorelessUnivariateStatistic implements Se * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> * <li>the start and length arguments do not determine a valid array</li> - * </ul></p> + * </ul> * <p> * Does not change the internal state of the statistic.</p> * @@ -541,9 +541,9 @@ public class Variance extends AbstractStorelessUnivariateStatistic implements Se * <p>Returns the weighted variance of the values in the input array, using * the precomputed weighted mean value.</p> * <p> - * Uses the formula <pre> + * Uses the formula <div style="white-space:pre"><code> * Σ(weights[i]*(values[i] - mean)<sup>2</sup>)/(Σ(weights[i]) - 1) - * </pre></p> + * </code></div> * <p> * The formula used assumes that the supplied mean value is the weighted arithmetic * mean of the sample data, not a known population parameter. This method @@ -567,7 +567,7 @@ public class Variance extends AbstractStorelessUnivariateStatistic implements Se * <li>the weights array contains one or more infinite values</li> * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> - * </ul></p> + * </ul> * <p> * Does not change the internal state of the statistic.</p> * http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/package-info.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/package-info.java b/src/main/java/org/apache/commons/math4/stat/descriptive/package-info.java index dd73f99..37397a4 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/package-info.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/package-info.java @@ -21,22 +21,22 @@ * <h3>UnivariateStatistic API Usage Examples:</h3> * * <h4>UnivariateStatistic:</h4> - * <code>/∗ evaluation approach ∗/<br/> - * double[] values = new double[] { 1, 2, 3, 4, 5 };<br/> - * <span style="font-weight: bold;">UnivariateStatistic stat = new Mean();</span><br/> - * out.println("mean = " + <span style="font-weight: bold;">stat.evaluate(values)</span>);<br/> + * <code>/∗ evaluation approach ∗/<br> + * double[] values = new double[] { 1, 2, 3, 4, 5 };<br> + * <span style="font-weight: bold;">UnivariateStatistic stat = new Mean();</span><br> + * out.println("mean = " + <span style="font-weight: bold;">stat.evaluate(values)</span>);<br> * </code> * * <h4>StorelessUnivariateStatistic:</h4> - * <code>/∗ incremental approach ∗/<br/> - * double[] values = new double[] { 1, 2, 3, 4, 5 };<br/> - * <span style="font-weight: bold;">StorelessUnivariateStatistic stat = new Mean();</span><br/> - * out.println("mean before adding a value is NaN = " + <span style="font-weight: bold;">stat.getResult()</span>);<br/> - * for (int i = 0; i < values.length; i++) {<br/> - * <span style="font-weight: bold;">stat.increment(values[i]);</span><br/> - * out.println("current mean = " + <span style="font-weight: bold;">stat2.getResult()</span>);<br/> - * }<br/> - * <span style="font-weight: bold;"> stat.clear();</span><br/> + * <code>/∗ incremental approach ∗/<br> + * double[] values = new double[] { 1, 2, 3, 4, 5 };<br> + * <span style="font-weight: bold;">StorelessUnivariateStatistic stat = new Mean();</span><br> + * out.println("mean before adding a value is NaN = " + <span style="font-weight: bold;">stat.getResult()</span>);<br> + * for (int i = 0; i < values.length; i++) {<br> + * <span style="font-weight: bold;">stat.increment(values[i]);</span><br> + * out.println("current mean = " + <span style="font-weight: bold;">stat2.getResult()</span>);<br> + * }<br> + * <span style="font-weight: bold;"> stat.clear();</span><br> * out.println("mean after clear is NaN = " + <span style="font-weight: bold;">stat.getResult()</span>); * </code> * http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Max.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Max.java b/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Max.java index 502d2d4..1615003 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Max.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Max.java @@ -26,13 +26,12 @@ import org.apache.commons.math4.util.MathUtils; /** * Returns the maximum of the available values. - * <p> * <ul> * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> * <li>If any of the values equals <code>Double.POSITIVE_INFINITY</code>, * the result is <code>Double.POSITIVE_INFINITY.</code></li> - * </ul></p> + * </ul> * <p> * <strong>Note that this implementation is not synchronized.</strong> If * multiple threads access an instance of this class concurrently, and at least @@ -112,13 +111,12 @@ public class Max extends AbstractStorelessUnivariateStatistic implements Seriali * <p> * Throws <code>MathIllegalArgumentException</code> if the array is null or * the array index parameters are not valid.</p> - * <p> * <ul> * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> * <li>If any of the values equals <code>Double.POSITIVE_INFINITY</code>, * the result is <code>Double.POSITIVE_INFINITY.</code></li> - * </ul></p> + * </ul> * * @param values the input array * @param begin index of the first array element to include http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Min.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Min.java b/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Min.java index 72eaef4..479a1f7 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Min.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Min.java @@ -26,13 +26,12 @@ import org.apache.commons.math4.util.MathUtils; /** * Returns the minimum of the available values. - * <p> * <ul> * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> * <li>If any of the values equals <code>Double.NEGATIVE_INFINITY</code>, * the result is <code>Double.NEGATIVE_INFINITY.</code></li> - * </ul></p> + * </ul> * <p> * <strong>Note that this implementation is not synchronized.</strong> If * multiple threads access an instance of this class concurrently, and at least @@ -112,13 +111,12 @@ public class Min extends AbstractStorelessUnivariateStatistic implements Seriali * <p> * Throws <code>MathIllegalArgumentException</code> if the array is null or * the array index parameters are not valid.</p> - * <p> * <ul> * <li>The result is <code>NaN</code> iff all values are <code>NaN</code> * (i.e. <code>NaN</code> values have no impact on the value of the statistic).</li> * <li>If any of the values equals <code>Double.NEGATIVE_INFINITY</code>, * the result is <code>Double.NEGATIVE_INFINITY.</code></li> - * </ul> </p> + * </ul> * * @param values the input array * @param begin index of the first array element to include http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/rank/PSquarePercentile.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/rank/PSquarePercentile.java b/src/main/java/org/apache/commons/math4/stat/descriptive/rank/PSquarePercentile.java index 7f3e54d..b6bdce5 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/rank/PSquarePercentile.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/rank/PSquarePercentile.java @@ -41,7 +41,7 @@ import org.apache.commons.numbers.core.Precision; /** * A {@link StorelessUnivariateStatistic} estimating percentiles using the - * <ahref=http://www.cs.wustl.edu/~jain/papers/ftp/psqr.pdf>P<SUP>2</SUP></a> + * <a href=http://www.cs.wustl.edu/~jain/papers/ftp/psqr.pdf>P<SUP>2</SUP></a> * Algorithm as explained by <a href=http://www.cse.wustl.edu/~jain/>Raj * Jain</a> and Imrich Chlamtac in * <a href=http://www.cse.wustl.edu/~jain/papers/psqr.htm>P<SUP>2</SUP> Algorithm http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Percentile.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Percentile.java b/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Percentile.java index a85fb63..c05d782 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Percentile.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/rank/Percentile.java @@ -43,20 +43,20 @@ import org.apache.commons.numbers.core.Precision; * significantly different results. The algorithm implemented here works as follows: * <ol> * <li>Let <code>n</code> be the length of the (sorted) array and - * <code>0 < p <= 100</code> be the desired percentile.</li> + * <code>0 < p <= 100</code> be the desired percentile.</li> * <li>If <code> n = 1 </code> return the unique array element (regardless of * the value of <code>p</code>); otherwise </li> * <li>Compute the estimated percentile position * <code> pos = p * (n + 1) / 100</code> and the difference, <code>d</code> * between <code>pos</code> and <code>floor(pos)</code> (i.e. the fractional * part of <code>pos</code>).</li> - * <li> If <code>pos < 1</code> return the smallest element in the array.</li> - * <li> Else if <code>pos >= n</code> return the largest element in the array.</li> + * <li> If <code>pos < 1</code> return the smallest element in the array.</li> + * <li> Else if <code>pos >= n</code> return the largest element in the array.</li> * <li> Else let <code>lower</code> be the element in position * <code>floor(pos)</code> in the array and let <code>upper</code> be the * next element in the array. Return <code>lower + d * (upper - lower)</code> * </li> - * </ol></p> + * </ol> * <p> * To compute percentiles, the data must be at least partially ordered. Input * arrays are copied and recursively partitioned using an ordering definition. @@ -247,7 +247,6 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa * <p> * Calls to this method do not modify the internal <code>quantile</code> * state of this statistic.</p> - * <p> * <ul> * <li>Returns <code>Double.NaN</code> if <code>values</code> has length * <code>0</code></li> @@ -256,7 +255,7 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa * <li>Throws <code>MathIllegalArgumentException</code> if <code>values</code> * is null or p is not a valid quantile value (p must be greater than 0 * and less than or equal to 100) </li> - * </ul></p> + * </ul> * <p> * See {@link Percentile} for a description of the percentile estimation * algorithm used.</p> @@ -277,14 +276,13 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa * Returns an estimate of the <code>quantile</code>th percentile of the * designated values in the <code>values</code> array. The quantile * estimated is determined by the <code>quantile</code> property. - * <p> * <ul> * <li>Returns <code>Double.NaN</code> if <code>length = 0</code></li> * <li>Returns (for any value of <code>quantile</code>) * <code>values[begin]</code> if <code>length = 1 </code></li> * <li>Throws <code>MathIllegalArgumentException</code> if <code>values</code> * is null, or <code>start</code> or <code>length</code> is invalid</li> - * </ul></p> + * </ul> * <p> * See {@link Percentile} for a description of the percentile estimation * algorithm used.</p> @@ -310,7 +308,6 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa * <p> * Calls to this method do not modify the internal <code>quantile</code> * state of this statistic.</p> - * <p> * <ul> * <li>Returns <code>Double.NaN</code> if <code>length = 0</code></li> * <li>Returns (for any value of <code>p</code>) <code>values[begin]</code> @@ -319,7 +316,7 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa * is null , <code>begin</code> or <code>length</code> is invalid, or * <code>p</code> is not a valid quantile value (p must be greater than 0 * and less than or equal to 100)</li> - * </ul></p> + * </ul> * <p> * See {@link Percentile} for a description of the percentile estimation * algorithm used.</p> @@ -367,7 +364,7 @@ public class Percentile extends AbstractUnivariateStatistic implements Serializa * Sets the value of the quantile field (determines what percentile is * computed when evaluate() is called with no quantile argument). * - * @param p a value between 0 < p <= 100 + * @param p a value between 0 < p <= 100 * @throws MathIllegalArgumentException if p is not greater than 0 and less * than or equal to 100 */ http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Product.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Product.java b/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Product.java index 5be6ce9..58609f8 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Product.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Product.java @@ -144,7 +144,7 @@ public class Product extends AbstractStorelessUnivariateStatistic implements Ser * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> * <li>the start and length arguments do not determine a valid array</li> - * </ul></p> + * </ul> * * <p>Uses the formula, <pre> * weighted product = ∏values[i]<sup>weights[i]</sup> @@ -182,7 +182,7 @@ public class Product extends AbstractStorelessUnivariateStatistic implements Ser * <li>the weights array contains one or more infinite values</li> * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> - * </ul></p> + * </ul> * * <p>Uses the formula, * <pre> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Sum.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Sum.java b/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Sum.java index bbe29fa..e112b5e 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Sum.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/summary/Sum.java @@ -143,11 +143,11 @@ public class Sum extends AbstractStorelessUnivariateStatistic implements Seriali * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> * <li>the start and length arguments do not determine a valid array</li> - * </ul></p> + * </ul> * <p> * Uses the formula, <pre> * weighted sum = Σ(values[i] * weights[i]) - * </pre></p> + * </pre> * * @param values the input array * @param weights the weights array @@ -179,11 +179,11 @@ public class Sum extends AbstractStorelessUnivariateStatistic implements Seriali * <li>the weights array contains one or more infinite values</li> * <li>the weights array contains one or more NaN values</li> * <li>the weights array contains negative values</li> - * </ul></p> + * </ul> * <p> * Uses the formula, <pre> * weighted sum = Σ(values[i] * weights[i]) - * </pre></p> + * </pre> * * @param values the input array * @param weights the weights array http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/descriptive/summary/SumOfLogs.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/descriptive/summary/SumOfLogs.java b/src/main/java/org/apache/commons/math4/stat/descriptive/summary/SumOfLogs.java index fcb00b9..75e7547 100644 --- a/src/main/java/org/apache/commons/math4/stat/descriptive/summary/SumOfLogs.java +++ b/src/main/java/org/apache/commons/math4/stat/descriptive/summary/SumOfLogs.java @@ -38,7 +38,7 @@ import org.apache.commons.math4.util.MathUtils; * <li>If both <code>Double.POSITIVE_INFINITY</code> and * <code>Double.NEGATIVE_INFINITY</code> are among the values, the result is * <code>NaN.</code></li> - * </ul></p> + * </ul> * <p> * <strong>Note that this implementation is not synchronized.</strong> If * multiple threads access an instance of this class concurrently, and at least http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/inference/BinomialTest.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/inference/BinomialTest.java b/src/main/java/org/apache/commons/math4/stat/inference/BinomialTest.java index d500311..2846c68 100644 --- a/src/main/java/org/apache/commons/math4/stat/inference/BinomialTest.java +++ b/src/main/java/org/apache/commons/math4/stat/inference/BinomialTest.java @@ -86,7 +86,7 @@ public class BinomialTest { * <li>Number of successes must be ≥ 0.</li> * <li>Number of successes must be ≤ number of trials.</li> * <li>Probability must be ≥ 0 and ≤ 1.</li> - * </ul></p> + * </ul> * * @param numberOfTrials number of trials performed * @param numberOfSuccesses number of successes observed http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/inference/ChiSquareTest.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/inference/ChiSquareTest.java b/src/main/java/org/apache/commons/math4/stat/inference/ChiSquareTest.java index add6c01..3836064 100644 --- a/src/main/java/org/apache/commons/math4/stat/inference/ChiSquareTest.java +++ b/src/main/java/org/apache/commons/math4/stat/inference/ChiSquareTest.java @@ -62,7 +62,7 @@ public class ChiSquareTest { * </li> * <li>The observed and expected arrays must have the same length and * their common length must be at least 2. - * </li></ul></p><p> + * </li></ul><p> * If any of the preconditions are not met, an * <code>IllegalArgumentException</code> is thrown.</p> * <p><strong>Note: </strong>This implementation rescales the @@ -135,7 +135,7 @@ public class ChiSquareTest { * </li> * <li>The observed and expected arrays must have the same length and * their common length must be at least 2. - * </li></ul></p><p> + * </li></ul><p> * If any of the preconditions are not met, an * <code>IllegalArgumentException</code> is thrown.</p> * <p><strong>Note: </strong>This implementation rescales the @@ -181,7 +181,7 @@ public class ChiSquareTest { * <li>The observed and expected arrays must have the same length and * their common length must be at least 2. * <li> <code> 0 < alpha < 0.5 </code> - * </li></ul></p><p> + * </li></ul><p> * If any of the preconditions are not met, an * <code>IllegalArgumentException</code> is thrown.</p> * <p><strong>Note: </strong>This implementation rescales the @@ -231,7 +231,7 @@ public class ChiSquareTest { * <li>The 2-way table represented by <code>counts</code> must have at * least 2 columns and at least 2 rows. * </li> - * </li></ul></p><p> + * </ul><p> * If any of the preconditions are not met, an * <code>IllegalArgumentException</code> is thrown.</p> * @@ -295,7 +295,7 @@ public class ChiSquareTest { * <li>The 2-way table represented by <code>counts</code> must have at least 2 * columns and at least 2 rows. * </li> - * </li></ul></p><p> + * </ul><p> * If any of the preconditions are not met, an * <code>IllegalArgumentException</code> is thrown.</p> * @@ -342,7 +342,7 @@ public class ChiSquareTest { * same length).</li> * <li>The 2-way table represented by <code>counts</code> must have at least 2 columns and * at least 2 rows.</li> - * </li></ul></p><p> + * </ul><p> * If any of the preconditions are not met, an * <code>IllegalArgumentException</code> is thrown.</p> * @@ -378,8 +378,8 @@ public class ChiSquareTest { * <code> * ∑[(K * observed1[i] - observed2[i]/K)<sup>2</sup> / (observed1[i] + observed2[i])] * </code> where - * <br/><code>K = &sqrt;[&sum(observed2 / ∑(observed1)]</code> - * </p> + * <br><code>K = √[∑(observed2 / ∑(observed1)]</code> + * * <p>This statistic can be used to perform a Chi-Square test evaluating the * null hypothesis that both observed counts follow the same distribution.</p> * <p> @@ -392,7 +392,7 @@ public class ChiSquareTest { * </li> * <li>The arrays <code>observed1</code> and <code>observed2</code> must have * the same length and their common length must be at least 2. - * </li></ul></p><p> + * </li></ul><p> * If any of the preconditions are not met, an * <code>IllegalArgumentException</code> is thrown.</p> * @@ -538,7 +538,7 @@ public class ChiSquareTest { * <li>The arrays <code>observed1</code> and <code>observed2</code> must * have the same length and their common length must be at least 2. * </li> - * <li> <code> 0 < alpha < 0.5 </code> + * <li> <code> 0 < alpha < 0.5 </code> * </li></ul><p> * If any of the preconditions are not met, an * <code>IllegalArgumentException</code> is thrown.</p> http://git-wip-us.apache.org/repos/asf/commons-math/blob/53ec46ba/src/main/java/org/apache/commons/math4/stat/inference/GTest.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/stat/inference/GTest.java b/src/main/java/org/apache/commons/math4/stat/inference/GTest.java index 0ee009d..0da2043 100644 --- a/src/main/java/org/apache/commons/math4/stat/inference/GTest.java +++ b/src/main/java/org/apache/commons/math4/stat/inference/GTest.java @@ -55,7 +55,7 @@ public class GTest { * <li>Expected counts must all be positive. </li> * <li>Observed counts must all be ≥ 0. </li> * <li>The observed and expected arrays must have the same length and their - * common length must be at least 2. </li></ul></p> + * common length must be at least 2. </li></ul> * * <p>If any of the preconditions are not met, a * {@code MathIllegalArgumentException} is thrown.</p> @@ -111,7 +111,7 @@ public class GTest { /** * Returns the <i>observed significance level</i>, or <a href= * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue";> p-value</a>, - * associated with a G-Test for goodness of fit</a> comparing the + * associated with a G-Test for goodness of fit comparing the * {@code observed} frequency counts to those in the {@code expected} array. * * <p>The number returned is the smallest significance level at which one @@ -128,7 +128,7 @@ public class GTest { * <li>Observed counts must all be ≥ 0. </li> * <li>The observed and expected arrays must have the * same length and their common length must be at least 2.</li> - * </ul></p> + * </ul> * * <p>If any of the preconditions are not met, a * {@code MathIllegalArgumentException} is thrown.</p> @@ -202,14 +202,14 @@ public class GTest { * {@code gTest(expected, observed, 0.01)}</p> * * <p>Returns true iff {@link #gTest(double[], long[]) - * gTestGoodnessOfFitPValue(expected, observed)} < alpha</p> + * gTestGoodnessOfFitPValue(expected, observed)} < alpha</p> * * <p><strong>Preconditions</strong>: <ul> * <li>Expected counts must all be positive. </li> * <li>Observed counts must all be ≥ 0. </li> * <li>The observed and expected arrays must have the same length and their * common length must be at least 2. - * <li> {@code 0 < alpha < 0.5} </li></ul></p> + * <li> {@code 0 < alpha < 0.5} </li></ul> * * <p>If any of the preconditions are not met, a * {@code MathIllegalArgumentException} is thrown.</p> @@ -279,8 +279,8 @@ public class GTest { /** * Calculates the <a href="http://en.wikipedia.org/wiki/Entropy_%28information_theory%29";> * Shannon entropy</a> for a vector. The values of {@code k} are taken to be - * incidence counts of the values of a random variable. What is returned is <br/> - * ∑p<sub>i</sub>log(p<sub>i</sub><br/> + * incidence counts of the values of a random variable. What is returned is <br> + * ∑p<sub>i</sub>log(p<sub>i</sub><br> * where p<sub>i</sub> = k[i] / (sum of elements in k) * * @param k Vector (for ex. Row Sums of a trials) @@ -314,8 +314,8 @@ public class GTest { * <p> where {@code H} is the * <a href="http://en.wikipedia.org/wiki/Entropy_%28information_theory%29";> * Shannon Entropy</a> of the random variable formed by viewing the elements - * of the argument array as incidence counts; <br/> - * {@code k} is a matrix with rows {@code [observed1, observed2]}; <br/> + * of the argument array as incidence counts; <br> + * {@code k} is a matrix with rows {@code [observed1, observed2]}; <br> * {@code rowSums, colSums} are the row/col sums of {@code k}; <br> * and {@code totalSum} is the overall sum of all entries in {@code k}.</p> * @@ -327,7 +327,7 @@ public class GTest { * <li>Observed counts for a specific bin must not both be zero. </li> * <li>Observed counts for a specific sample must not all be 0. </li> * <li>The arrays {@code observed1} and {@code observed2} must have - * the same length and their common length must be at least 2. </li></ul></p> + * the same length and their common length must be at least 2. </li></ul> * * <p>If any of the preconditions are not met, a * {@code MathIllegalArgumentException} is thrown.</p> @@ -398,7 +398,7 @@ public class GTest { * * <p>{@code (sgn) sqrt(gValueDataSetsComparison({k11, k12}, {k21, k22})}</p> * - * <p>where {@code sgn} is -1 if {@code k11 / (k11 + k12) < k21 / (k21 + k22))};<br/> + * <p>where {@code sgn} is -1 if {@code k11 / (k11 + k12) < k21 / (k21 + k22))};<br> * 1 otherwise.</p> * * <p>Signed root LLR has two advantages over the basic LLR: a) it is positive @@ -450,7 +450,7 @@ public class GTest { * <li>Observed counts for a specific sample must not all be 0. </li> * <li>The arrays {@code observed1} and {@code observed2} must * have the same length and their common length must be at least 2. </li> - * </ul><p> + * </ul> * <p> If any of the preconditions are not met, a * {@code MathIllegalArgumentException} is thrown.</p> * @@ -500,7 +500,7 @@ public class GTest { * <li>Observed counts for a specific sample must not all be 0. </li> * <li>The arrays {@code observed1} and {@code observed2} must * have the same length and their common length must be at least 2. </li> - * <li>{@code 0 < alpha < 0.5} </li></ul></p> + * <li>{@code 0 < alpha < 0.5} </li></ul> * * <p>If any of the preconditions are not met, a * {@code MathIllegalArgumentException} is thrown.</p>
