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Posted to commits@commons.apache.org by tn...@apache.org on 2013/05/27 22:22:49 UTC
svn commit: r1486708 -
/commons/proper/math/trunk/src/site/xdoc/userguide/random.xml
Author: tn
Date: Mon May 27 20:22:48 2013
New Revision: 1486708
URL: http://svn.apache.org/r1486708
Log:
Add reference to the java code used to generate the figure.
Modified:
commons/proper/math/trunk/src/site/xdoc/userguide/random.xml
Modified: commons/proper/math/trunk/src/site/xdoc/userguide/random.xml
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/site/xdoc/userguide/random.xml?rev=1486708&r1=1486707&r2=1486708&view=diff
==============================================================================
--- commons/proper/math/trunk/src/site/xdoc/userguide/random.xml (original)
+++ commons/proper/math/trunk/src/site/xdoc/userguide/random.xml Mon May 27 20:22:48 2013
@@ -246,8 +246,10 @@ RandomVectorGenerator generator = new So
// Use the generator to generate vectors
double[] randomVector = generator.nextVector();
... </source>
- The figure below illustrates the unique properties of low-discrepancy sequences when generating N samples in the interval [0, 1].
- Roughly speaking, such sequences fill up the respective space more evenly which leads to faster convergence in quasi-Monte Carlo simulations.
+ The figure below (created with <a href="../xref-test/org/apache/commons/math3/userguide/LowDiscrepancyGeneratorComparison.html">
+ LowDiscrepancyGeneratorComparison.java</a>) illustrates the unique properties of low-discrepancy sequences when generating N samples
+ in the interval [0, 1]. Roughly speaking, such sequences "fill" the respective space more evenly which leads to faster convergence in
+ quasi-Monte Carlo simulations.
<img src="../images/userguide/low_discrepancy_sequences.png" alt="Comparison of low-discrepancy sequences"/>
</dd></dl>
</p>