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 <h2 title="Class HypergeometricDistribution" class="title">Class HypergeometricDistribution</h2>
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 <li>org.apache.commons.math3.distribution.HypergeometricDistribution</li>
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 <pre>public class <span class="strong">HypergeometricDistribution</span>
 extends <a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractIntegerDistribution</a></pre>
 <div class="block">Implementation of the hypergeometric distribution.</div>
 <dl><dt><span class="strong">Version:</span></dt>
   <dd>$Id: HypergeometricDistribution.java 1534358 2013-10-21 20:13:52Z tn $</dd>
 <dt><span class="strong">See Also:</span></dt><dd><a href="http://en.wikipedia.org/wiki/Hypergeometric_distribution">Hypergeometric distribution (Wikipedia)</a>,
 <a href="http://mathworld.wolfram.com/HypergeometricDistribution.html">Hypergeometric distribution (MathWorld)</a>,
 <a href="../../../../../serialized-form.html#org.apache.commons.math3.distribution.HypergeometricDistribution">Serialized Form</a></dd></dl>
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 <code><a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#random">random</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#randomData">randomData</a></code></li>
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 <th class="colOne" scope="col">Constructor and Description</th>
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 <td class="colOne"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#HypergeometricDistribution(int, int, int)">HypergeometricDistribution</a></strong>(int&nbsp;populationSize,
                           int&nbsp;numberOfSuccesses,
                           int&nbsp;sampleSize)</code>
 <div class="block">Construct a new hypergeometric distribution with the specified population
  size, number of successes in the population, and sample size.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colOne"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#HypergeometricDistribution(org.apache.commons.math3.random.RandomGenerator, int, int, int)">HypergeometricDistribution</a></strong>(<a href="../../../../../org/apache/commons/math3/random/RandomGenerator.html" title="interface in org.apache.commons.math3.random">RandomGenerator</a>&nbsp;rng,
                           int&nbsp;populationSize,
                           int&nbsp;numberOfSuccesses,
                           int&nbsp;sampleSize)</code>
 <div class="block">Creates a new hypergeometric distribution.</div>
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 <th class="colFirst" scope="col">Modifier and Type</th>
 <th class="colLast" scope="col">Method and Description</th>
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 <td class="colFirst"><code>protected double</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#calculateNumericalVariance()">calculateNumericalVariance</a></strong>()</code>
 <div class="block">Used by <a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getNumericalVariance()"><code>getNumericalVariance()</code></a>.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><code>double</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#cumulativeProbability(int)">cumulativeProbability</a></strong>(int&nbsp;x)</code>
 <div class="block">For a random variable <code>X</code> whose values are distributed according
  to this distribution, this method returns <code>P(X &lt;= x)</code>.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><code>int</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getNumberOfSuccesses()">getNumberOfSuccesses</a></strong>()</code>
 <div class="block">Access the number of successes.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><code>double</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getNumericalMean()">getNumericalMean</a></strong>()</code>
 <div class="block">Use this method to get the numerical value of the mean of this
  distribution.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><code>double</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getNumericalVariance()">getNumericalVariance</a></strong>()</code>
 <div class="block">Use this method to get the numerical value of the variance of this
  distribution.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><code>int</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getPopulationSize()">getPopulationSize</a></strong>()</code>
 <div class="block">Access the population size.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><code>int</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getSampleSize()">getSampleSize</a></strong>()</code>
 <div class="block">Access the sample size.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><code>int</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getSupportLowerBound()">getSupportLowerBound</a></strong>()</code>
 <div class="block">Access the lower bound of the support.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><code>int</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getSupportUpperBound()">getSupportUpperBound</a></strong>()</code>
 <div class="block">Access the upper bound of the support.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><code>boolean</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#isSupportConnected()">isSupportConnected</a></strong>()</code>
 <div class="block">Use this method to get information about whether the support is
  connected, i.e.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><code>double</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#logProbability(int)">logProbability</a></strong>(int&nbsp;x)</code>
 <div class="block">For a random variable <code>X</code> whose values are distributed according to
  this distribution, this method returns <code>log(P(X = x))</code>, where
  <code>log</code> is the natural logarithm.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><code>double</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#probability(int)">probability</a></strong>(int&nbsp;x)</code>
 <div class="block">For a random variable <code>X</code> whose values are distributed according
  to this distribution, this method returns <code>P(X = x)</code>.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><code>double</code></td>
 <td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#upperCumulativeProbability(int)">upperCumulativeProbability</a></strong>(int&nbsp;x)</code>
 <div class="block">For this distribution, <code>X</code>, this method returns <code>P(X &gt;= x)</code>.</div>
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 <h3>Methods inherited from class&nbsp;org.apache.commons.math3.distribution.<a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractIntegerDistribution</a></h3>
 <code><a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#cumulativeProbability(int, int)">cumulativeProbability</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#inverseCumulativeProbability(double)">inverseCumulativeProbability</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#reseedRandomGenerator(long)">reseedRandomGenerator</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#sample()">sample</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#sample(int)">sample</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#solveInverseCumulativeProbability(double, int, int)">solveInverseCumulativeProbability</a></code></li>
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 <h4>HypergeometricDistribution</h4>
 <pre>public&nbsp;HypergeometricDistribution(int&nbsp;populationSize,
                           int&nbsp;numberOfSuccesses,
                           int&nbsp;sampleSize)
                            throws <a href="../../../../../org/apache/commons/math3/exception/NotPositiveException.html" title="class in org.apache.commons.math3.exception">NotPositiveException</a>,
                                   <a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a>,
                                   <a href="../../../../../org/apache/commons/math3/exception/NumberIsTooLargeException.html" title="class in org.apache.commons.math3.exception">NumberIsTooLargeException</a></pre>
 <div class="block">Construct a new hypergeometric distribution with the specified population
  size, number of successes in the population, and sample size.</div>
 <dl><dt><span class="strong">Parameters:</span></dt><dd><code>populationSize</code> - Population size.</dd><dd><code>numberOfSuccesses</code> - Number of successes in the population.</dd><dd><code>sampleSize</code> - Sample size.</dd>
 <dt><span class="strong">Throws:</span></dt>
 <dd><code><a href="../../../../../org/apache/commons/math3/exception/NotPositiveException.html" title="class in org.apache.commons.math3.exception">NotPositiveException</a></code> - if <code>numberOfSuccesses &lt; 0</code>.</dd>
 <dd><code><a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></code> - if <code>populationSize &lt;= 0</code>.</dd>
 <dd><code><a href="../../../../../org/apache/commons/math3/exception/NumberIsTooLargeException.html" title="class in org.apache.commons.math3.exception">NumberIsTooLargeException</a></code> - if <code>numberOfSuccesses &gt; populationSize</code>,
  or <code>sampleSize &gt; populationSize</code>.</dd></dl>
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 <pre>public&nbsp;HypergeometricDistribution(<a href="../../../../../org/apache/commons/math3/random/RandomGenerator.html" title="interface in org.apache.commons.math3.random">RandomGenerator</a>&nbsp;rng,
                           int&nbsp;populationSize,
                           int&nbsp;numberOfSuccesses,
                           int&nbsp;sampleSize)
                            throws <a href="../../../../../org/apache/commons/math3/exception/NotPositiveException.html" title="class in org.apache.commons.math3.exception">NotPositiveException</a>,
                                   <a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a>,
                                   <a href="../../../../../org/apache/commons/math3/exception/NumberIsTooLargeException.html" title="class in org.apache.commons.math3.exception">NumberIsTooLargeException</a></pre>
 <div class="block">Creates a new hypergeometric distribution.</div>
 <dl><dt><span class="strong">Parameters:</span></dt><dd><code>rng</code> - Random number generator.</dd><dd><code>populationSize</code> - Population size.</dd><dd><code>numberOfSuccesses</code> - Number of successes in the population.</dd><dd><code>sampleSize</code> - Sample size.</dd>
 <dt><span class="strong">Throws:</span></dt>
 <dd><code><a href="../../../../../org/apache/commons/math3/exception/NotPositiveException.html" title="class in org.apache.commons.math3.exception">NotPositiveException</a></code> - if <code>numberOfSuccesses &lt; 0</code>.</dd>
 <dd><code><a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></code> - if <code>populationSize &lt;= 0</code>.</dd>
 <dd><code><a href="../../../../../org/apache/commons/math3/exception/NumberIsTooLargeException.html" title="class in org.apache.commons.math3.exception">NumberIsTooLargeException</a></code> - if <code>numberOfSuccesses &gt; populationSize</code>,
  or <code>sampleSize &gt; populationSize</code>.</dd><dt><span class="strong">Since:</span></dt>
   <dd>3.1</dd></dl>
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 <pre>public&nbsp;double&nbsp;cumulativeProbability(int&nbsp;x)</pre>
 <div class="block">For a random variable <code>X</code> whose values are distributed according
  to this distribution, this method returns <code>P(X &lt;= x)</code>.  In other
  words, this method represents the (cumulative) distribution function
  (CDF) for this distribution.</div>
 <dl><dt><span class="strong">Parameters:</span></dt><dd><code>x</code> - the point at which the CDF is evaluated</dd>
 <dt><span class="strong">Returns:</span></dt><dd>the probability that a random variable with this
  distribution takes a value less than or equal to <code>x</code></dd></dl>
 </li>
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 <pre>public&nbsp;int&nbsp;getNumberOfSuccesses()</pre>
 <div class="block">Access the number of successes.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd>the number of successes.</dd></dl>
 </li>
 </ul>
 <a name="getPopulationSize()">
 <!--   -->
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 <pre>public&nbsp;int&nbsp;getPopulationSize()</pre>
 <div class="block">Access the population size.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd>the population size.</dd></dl>
 </li>
 </ul>
 <a name="getSampleSize()">
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 <h4>getSampleSize</h4>
 <pre>public&nbsp;int&nbsp;getSampleSize()</pre>
 <div class="block">Access the sample size.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd>the sample size.</dd></dl>
 </li>
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 <h4>probability</h4>
 <pre>public&nbsp;double&nbsp;probability(int&nbsp;x)</pre>
 <div class="block">For a random variable <code>X</code> whose values are distributed according
  to this distribution, this method returns <code>P(X = x)</code>. In other
  words, this method represents the probability mass function (PMF)
  for the distribution.</div>
 <dl><dt><span class="strong">Parameters:</span></dt><dd><code>x</code> - the point at which the PMF is evaluated</dd>
 <dt><span class="strong">Returns:</span></dt><dd>the value of the probability mass function at <code>x</code></dd></dl>
 </li>
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 <pre>public&nbsp;double&nbsp;logProbability(int&nbsp;x)</pre>
 <div class="block">For a random variable <code>X</code> whose values are distributed according to
  this distribution, this method returns <code>log(P(X = x))</code>, where
  <code>log</code> is the natural logarithm. In other words, this method
  represents the logarithm of the probability mass function (PMF) for the
  distribution. Note that due to the floating point precision and
  under/overflow issues, this method will for some distributions be more
  precise and faster than computing the logarithm of
  <a href="../../../../../org/apache/commons/math3/distribution/IntegerDistribution.html#probability(int)"><code>IntegerDistribution.probability(int)</code></a>.
  <p>
  The default implementation simply computes the logarithm of <code>probability(x)</code>.</p></div>
 <dl>
 <dt><strong>Overrides:</strong></dt>
 <dd><code><a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html#logProbability(int)">logProbability</a></code>&nbsp;in class&nbsp;<code><a href="../../../../../org/apache/commons/math3/distribution/AbstractIntegerDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractIntegerDistribution</a></code></dd>
 <dt><span class="strong">Parameters:</span></dt><dd><code>x</code> - the point at which the PMF is evaluated</dd>
 <dt><span class="strong">Returns:</span></dt><dd>the logarithm of the value of the probability mass function at <code>x</code></dd></dl>
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 <pre>public&nbsp;double&nbsp;upperCumulativeProbability(int&nbsp;x)</pre>
 <div class="block">For this distribution, <code>X</code>, this method returns <code>P(X &gt;= x)</code>.</div>
 <dl><dt><span class="strong">Parameters:</span></dt><dd><code>x</code> - Value at which the CDF is evaluated.</dd>
 <dt><span class="strong">Returns:</span></dt><dd>the upper tail CDF for this distribution.</dd><dt><span class="strong">Since:</span></dt>
   <dd>1.1</dd></dl>
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 <h4>getNumericalMean</h4>
 <pre>public&nbsp;double&nbsp;getNumericalMean()</pre>
 <div class="block">Use this method to get the numerical value of the mean of this
  distribution.

  For population size <code>N</code>, number of successes <code>m</code>, and sample
  size <code>n</code>, the mean is <code>n * m / N</code>.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd>the mean or <code>Double.NaN</code> if it is not defined</dd></dl>
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 <pre>public&nbsp;double&nbsp;getNumericalVariance()</pre>
 <div class="block">Use this method to get the numerical value of the variance of this
  distribution.

  For population size <code>N</code>, number of successes <code>m</code>, and sample
  size <code>n</code>, the variance is
  <code>[n * m * (N - n) * (N - m)] / [N^2 * (N - 1)]</code>.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd>the variance (possibly <code>Double.POSITIVE_INFINITY</code> or
  <code>Double.NaN</code> if it is not defined)</dd></dl>
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 <pre>protected&nbsp;double&nbsp;calculateNumericalVariance()</pre>
 <div class="block">Used by <a href="../../../../../org/apache/commons/math3/distribution/HypergeometricDistribution.html#getNumericalVariance()"><code>getNumericalVariance()</code></a>.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd>the variance of this distribution</dd></dl>
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 <pre>public&nbsp;int&nbsp;getSupportLowerBound()</pre>
 <div class="block">Access the lower bound of the support. This method must return the same
  value as <code>inverseCumulativeProbability(0)</code>. In other words, this
  method must return
  <p><code>inf {x in Z | P(X <= x) > 0}</code>.</p>

  For population size <code>N</code>, number of successes <code>m</code>, and sample
  size <code>n</code>, the lower bound of the support is
  <code>max(0, n + m - N)</code>.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd>lower bound of the support</dd></dl>
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 <pre>public&nbsp;int&nbsp;getSupportUpperBound()</pre>
 <div class="block">Access the upper bound of the support. This method must return the same
  value as <code>inverseCumulativeProbability(1)</code>. In other words, this
  method must return
  <p><code>inf {x in R | P(X <= x) = 1}</code>.</p>

  For number of successes <code>m</code> and sample size <code>n</code>, the upper
  bound of the support is <code>min(m, n)</code>.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd>upper bound of the support</dd></dl>
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 <pre>public&nbsp;boolean&nbsp;isSupportConnected()</pre>
 <div class="block">Use this method to get information about whether the support is
  connected, i.e. whether all integers between the lower and upper bound of
  the support are included in the support.

  The support of this distribution is connected.</div>
 <dl><dt><span class="strong">Returns:</span></dt><dd><code>true</code></dd></dl>
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