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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>