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Posted to commits@commons.apache.org by ps...@apache.org on 2014/05/24 23:22:00 UTC
svn commit: r1597357 -
/commons/proper/math/trunk/src/site/xdoc/userguide/distribution.xml
Author: psteitz
Date: Sat May 24 21:21:59 2014
New Revision: 1597357
URL: http://svn.apache.org/r1597357
Log:
Added some info on sampling.
Modified:
commons/proper/math/trunk/src/site/xdoc/userguide/distribution.xml
Modified: commons/proper/math/trunk/src/site/xdoc/userguide/distribution.xml
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/site/xdoc/userguide/distribution.xml?rev=1597357&r1=1597356&r2=1597357&view=diff
==============================================================================
--- commons/proper/math/trunk/src/site/xdoc/userguide/distribution.xml (original)
+++ commons/proper/math/trunk/src/site/xdoc/userguide/distribution.xml Sat May 24 21:21:59 2014
@@ -28,7 +28,16 @@
<subsection name="8.1 Overview" href="overview">
<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>
An overview of available continuous distributions:<br/>
@@ -42,7 +51,8 @@
(<code>probability(·)</code>) and distribution functions
(<code>cumulativeProbability(·)</code>) 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>
For an instance <code>f</code> of a distribution <code>F</code>,
@@ -63,6 +73,14 @@
double lowerTail = t.cumulativeProbability(-2.656); // P(T(29) <= -2.656)
double upperTail = 1.0 - t.cumulativeProbability(2.75); // P(T(29) >= 2.75)</source>
<p>
+ All distributions implement a <code>sample()</code> 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 <code>RandomGenerator</code> constructor argument will avoid the overhead of initializing
+ the default generator.
+ </p>
+ <p>
Inverse distribution functions can be computed using the
<code>inverseCumulativeProbability</code> methods. For continuous <code>f</code>
and <code>p</code> a probability, <code>f.inverseCumulativeProbability(p)</code> returns