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fixed typos 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@608890 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Luc Maisonobe 2008-01-04 15:41:38 +00:00
parent 70e682b211
commit e8ba93825d
1 changed files with 5 additions and 5 deletions
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10
xdocs/userguide/random.xml
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@ -117,7 +117,7 @@
For the non-secure methods, starting with the same seed always produces the
same sequence of values. Secure sequences started with the same seeds will
diverge. When a new <code>RandomDataImpl</code> is created, the underlying
random number generators are <strong>not</strong> intialized. The first
random number generators are <strong>not</strong> initialized. The first
call to a data generation method, or to a <code>reSeed()</code> method
initializes the appropriate generator. If you do not explicitly seed the
generator, it is by default seeded with the current time in milliseconds.
@ -176,15 +176,15 @@ for (int i = 0; i &lt; 1000; i++) {
however, generating them is much more difficult. The <a
href="../apidocs/org/apache/commons/math/random/CorrelatedRandomVectorGenerator.html">
org.apache.commons.math.CorrelatedRandomVectorGenerator</a> class
provides this service. In this case, the user must set a complete covariance matrix
instead of a simple standard deviations vector, this matrix gather both the variance
provides this service. In this case, the user must set up a complete covariance matrix
instead of a simple standard deviations vector. This matrix gathers both the variance
and the correlation information of the probability law.
</p>
<p>
The main use for correlated random vector generation is for Monte-Carlo
simulation of physical problems with several variables, for example to
generate error vectors to be added to a nominal vector. A particularly
interesting case is when the generated vector should be drawn from a <a
common case is when the generated vector should be drawn from a <a
href="http://en.wikipedia.org/wiki/Multivariate_normal_distribution">
Multivariate Normal Distribution</a>.
</p>
@ -226,7 +226,7 @@ for (int i = 0; i &lt; 1000; i++) {
To select a random sample of objects in a collection, you can use the
<code>nextSample</code> method in the <code>RandomData</code> interface.
Specifically, if <code>c</code> is a collection containing at least
<code>k</code> objects, and <code>ranomData</code> is a
<code>k</code> objects, and <code>randomData</code> is a
<code>RandomData</code> instance <code>randomData.nextSample(c, k)</code>
will return an <code>object[]</code> array of length <code>k</code>
consisting of elements randomly selected from the collection. If