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commit b44c2610e0991cbe155d647065abf11d3d39fa8d Author: Gilles Sadowski <[email protected]> AuthorDate: Sat Sep 18 03:05:51 2021 +0200 Javadoc. --- .../legacy/distribution/EmpiricalDistribution.java | 34 +++++++++------------- 1 file changed, 13 insertions(+), 21 deletions(-) diff --git a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EmpiricalDistribution.java b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EmpiricalDistribution.java index 0c72c0a..7929378 100644 --- a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EmpiricalDistribution.java +++ b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EmpiricalDistribution.java @@ -34,25 +34,25 @@ import org.apache.commons.math4.legacy.core.jdkmath.AccurateMath; /** * <p>Represents an <a href="http://en.wikipedia.org/wiki/Empirical_distribution_function";> * empirical probability distribution</a>: Probability distribution derived - * from observed data without making any assumptions about the functional form - * of the population distribution that the data come from.</p> + * from observed data without making any assumptions about the functional + * form of the population distribution that the data come from.</p> * * <p>An {@code EmpiricalDistribution} maintains data structures called * <i>distribution digests</i> that describe empirical distributions and * support the following operations: * <ul> - * <li>loading the distribution from a file of observed data values</li> - * <li>dividing the input data into "bin ranges" and reporting bin frequency - * counts (data for histogram)</li> - * <li>reporting univariate statistics describing the full set of data values - * as well as the observations within each bin</li> + * <li>loading the distribution from "observed" data values</li> + * <li>dividing the input data into "bin ranges" and reporting bin + * frequency counts (data for histogram)</li> + * <li>reporting univariate statistics describing the full set of data + * values as well as the observations within each bin</li> * <li>generating random values from the distribution</li> * </ul> * * Applications can use {@code EmpiricalDistribution} to build grouped - * frequency histograms representing the input data or to generate random values - * "like" those in the input file, i.e. the values generated will follow the - * distribution of the values in the file. + * frequency histograms representing the input data or to generate random + * values "like" those in the input, i.e. the values generated will follow + * the distribution of the values in the file. * * <p>The implementation uses what amounts to the * <a href="http://nedwww.ipac.caltech.edu/level5/March02/Silverman/Silver2_6.html";> @@ -84,16 +84,8 @@ import org.apache.commons.math4.legacy.core.jdkmath.AccurateMath; * grouped frequency distribution at the bin endpoints and interpolates within * bins using within-bin kernels.</p> * - * <strong>USAGE NOTES:</strong> - * <ul> - * <li> - * The {@code binCount} is set by default to 1000. A good rule of thumb - * is to set the bin count to approximately the length of the input file - * divided by 10. </li> - * <li> - * The input file <i>must</i> be a plain text file containing one valid - * numeric entry per line.</li> - * </ul> + * <strong>CAVEAT</strong>: It is advised that the {@link #from(int,double[]) + * bin count} is about one tenth of the size of the input array. */ public final class EmpiricalDistribution extends AbstractRealDistribution implements ContinuousDistribution { @@ -547,7 +539,7 @@ public final class EmpiricalDistribution extends AbstractRealDistribution /** * The within-bin smoothing kernel: A Gaussian distribution - * (unless the bin contains only one observation, in which case + * (unless the bin contains 0 or 1 observation, in which case * a constant distribution is returned). * * @return the within-bin kernel factory.
