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From pste...@apache.org
Subject svn commit: r909861 - /websites/production/commons/content/proper/commons-math/userguide/distribution.html
Date Sun, 25 May 2014 05:46:23 GMT
Author: psteitz
Date: Sun May 25 05:46:23 2014
New Revision: 909861

Log:
Added some info on sampling.

Modified:
    websites/production/commons/content/proper/commons-math/userguide/distribution.html

Modified: websites/production/commons/content/proper/commons-math/userguide/distribution.html
==============================================================================
--- websites/production/commons/content/proper/commons-math/userguide/distribution.html (original)
+++ websites/production/commons/content/proper/commons-math/userguide/distribution.html Sun
May 25 05:46:23 2014
@@ -1,13 +1,13 @@
 <!DOCTYPE html>
 <!--
- | Generated by Apache Maven Doxia at 15 May 2014
+ | Generated by Apache Maven Doxia at 24 May 2014
  | Rendered using Apache Maven Fluido Skin 1.3.0
 -->
 <html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
   <head>
     <meta charset="UTF-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <meta name="Date-Revision-yyyymmdd" content="20140515" />
+    <meta name="Date-Revision-yyyymmdd" content="20140524" />
     <meta http-equiv="Content-Language" content="en" />
     <title>Math - 
     The Commons Math User Guide - Distributions</title>
@@ -41,7 +41,7 @@
 					<a class="brand" href="http://commons.apache.org/proper/commons-math/">Apache
Commons Math &trade;</a>
 					<ul class="nav">      
                     
-            <li id="publishDate">Last Published: 15 May 2014</li>
+            <li id="publishDate">Last Published: 24 May 2014</li>
       <li class="divider">|</li> <li id="projectVersion">Version: 3.3</li>
   </ul>
                     <div class="pull-right">	<ul class="nav">
@@ -320,7 +320,16 @@
         
 <p>
           The distributions package provides a framework and implementations for some commonly
used
-          probability distributions.
+          probability distributions. Continuous univariate distributions are represented
by implementations of
+          the <a href="../apidocs/org/apache/commons/math3/distribution/RealDistribution.html">RealDistribution</a>
+          interface.  Discrete distributions implement
+          <a href="../apidocs/org/apache/commons/math3/distribution/IntegerDistribution.html">IntegerDistribution</a>
+          (values must be mapped to integers) and there is an
+          <a href="../apidocs/org/apache/commons/math3/distribution/EnumeratedDistribution.html">EnumeratedDistribution</a>
+          class representing discrete distributions with a finite, enumerated set of values.
 Finally, multivariate
+          real-valued distributions can be represented via the 
+          <a href="../apidocs/org/apache/commons/math3/distribution/MultiVariateRealDistribution.html">MultivariateRealDistribution</a>
+          interface.
         </p>
         
 <p>
@@ -338,7 +347,8 @@
           (<tt>probability(&#xb7;)</tt>) and distribution functions
           (<tt>cumulativeProbability(&#xb7;)</tt>) for both
           discrete (integer-valued) and continuous probability distributions.
-          The framework also allows for the computation of inverse cumulative probabilities.
+          The framework also allows for the computation of inverse cumulative probabilities
+          and sampling from distributions.
         </p>
         
 <p>
@@ -363,6 +373,15 @@ double lowerTail = t.cumulativeProbabili
 double upperTail = 1.0 - t.cumulativeProbability(2.75); // P(T(29) &gt;= 2.75)</pre></div>
         
 <p>
+          All distributions implement a <tt>sample()</tt> method to support random
sampling from the
+          distribution. Implementation classes expose constructors allowing the default 
+          <a href="../apidocs/org/apache/commons/math3/random/RandomGenerator.html">RandomGenerator</a>
+          used by the sampling algorithm to be overridden.  If sampling is not going to be
used, providing
+          a null <tt>RandomGenerator</tt> constructor argument will avoid the
overhead of initializing
+          the default generator.
+        </p>
+        
+<p>
           Inverse distribution functions can be computed using the
           <tt>inverseCumulativeProbability</tt> methods.  For continuous <tt>f</tt>
           and <tt>p</tt> a probability, <tt>f.inverseCumulativeProbability(p)</tt>
returns
@@ -417,4 +436,4 @@ double upperTail = 1.0 - t.cumulativePro
                           		</div>
 	</body>
 
-</html>
\ No newline at end of file
+</html>



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