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<div class="subTitle">org.apache.commons.math3.distribution</div>
<h2 title="Class ParetoDistribution" class="title">Class ParetoDistribution</h2>
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<li><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html" title="class in org.apache.commons.math3.distribution">org.apache.commons.math3.distribution.AbstractRealDistribution</a></li>
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<ul class="inheritance">
<li>org.apache.commons.math3.distribution.ParetoDistribution</li>
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<dd><a href="http://docs.oracle.com/javase/6/docs/api/java/io/Serializable.html?is-external=true" title="class or interface in java.io">Serializable</a>, <a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html" title="interface in org.apache.commons.math3.distribution">RealDistribution</a></dd>
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<pre>public class <span class="strong">ParetoDistribution</span>
extends <a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractRealDistribution</a></pre>
<div class="block">Implementation of the Pareto distribution.
<p>
<strong>Parameters:</strong>
The probability distribution function of <code>X</code> is given by (for <code>x &gt;= k</code>):
<pre>
α * k^α / x^(α + 1)
</pre>
<p>
<ul>
<li><code>k</code> is the <em>scale</em> parameter: this is the minimum possible value of <code>X</code>,</li>
<li><code>α</code> is the <em>shape</em> parameter: this is the Pareto index</li>
</ul></div>
<dl><dt><span class="strong">Since:</span></dt>
<dd>3.3</dd>
<dt><span class="strong">Version:</span></dt>
<dd>$Id: ParetoDistribution.java 1533974 2013-10-20 20:42:41Z psteitz $</dd>
<dt><span class="strong">See Also:</span></dt><dd><a href="http://en.wikipedia.org/wiki/Pareto_distribution">
Pareto distribution (Wikipedia)</a>,
<a href="http://mathworld.wolfram.com/ParetoDistribution.html">
Pareto distribution (MathWorld)</a>,
<a href="../../../../../serialized-form.html#org.apache.commons.math3.distribution.ParetoDistribution">Serialized Form</a></dd></dl>
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<th class="colFirst" scope="col">Modifier and Type</th>
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<td class="colFirst"><code>static double</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#DEFAULT_INVERSE_ABSOLUTE_ACCURACY">DEFAULT_INVERSE_ABSOLUTE_ACCURACY</a></strong></code>
<div class="block">Default inverse cumulative probability accuracy.</div>
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<h3>Fields inherited from class&nbsp;org.apache.commons.math3.distribution.<a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractRealDistribution</a></h3>
<code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#random">random</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#randomData">randomData</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#SOLVER_DEFAULT_ABSOLUTE_ACCURACY">SOLVER_DEFAULT_ABSOLUTE_ACCURACY</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/ParetoDistribution.html#ParetoDistribution()">ParetoDistribution</a></strong>()</code>
<div class="block">Create a Pareto distribution with a scale of <code>1</code> and a shape of <code>1</code>.</div>
</td>
</tr>
<tr class="rowColor">
<td class="colOne"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#ParetoDistribution(double, double)">ParetoDistribution</a></strong>(double&nbsp;scale,
double&nbsp;shape)</code>
<div class="block">Create a Pareto distribution using the specified scale and shape.</div>
</td>
</tr>
<tr class="altColor">
<td class="colOne"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#ParetoDistribution(double, double, double)">ParetoDistribution</a></strong>(double&nbsp;scale,
double&nbsp;shape,
double&nbsp;inverseCumAccuracy)</code>
<div class="block">Create a Pareto distribution using the specified scale, shape and
inverse cumulative distribution accuracy.</div>
</td>
</tr>
<tr class="rowColor">
<td class="colOne"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#ParetoDistribution(org.apache.commons.math3.random.RandomGenerator, double, double)">ParetoDistribution</a></strong>(<a href="../../../../../org/apache/commons/math3/random/RandomGenerator.html" title="interface in org.apache.commons.math3.random">RandomGenerator</a>&nbsp;rng,
double&nbsp;scale,
double&nbsp;shape)</code>
<div class="block">Creates a log-normal distribution.</div>
</td>
</tr>
<tr class="altColor">
<td class="colOne"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#ParetoDistribution(org.apache.commons.math3.random.RandomGenerator, double, double, double)">ParetoDistribution</a></strong>(<a href="../../../../../org/apache/commons/math3/random/RandomGenerator.html" title="interface in org.apache.commons.math3.random">RandomGenerator</a>&nbsp;rng,
double&nbsp;scale,
double&nbsp;shape,
double&nbsp;inverseCumAccuracy)</code>
<div class="block">Creates a log-normal distribution.</div>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#cumulativeProbability(double)">cumulativeProbability</a></strong>(double&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="rowColor">
<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#cumulativeProbability(double, double)">cumulativeProbability</a></strong>(double&nbsp;x0,
double&nbsp;x1)</code>
<div class="block"><strong>Deprecated.</strong>&nbsp;
<div class="block"><i>See <a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html#cumulativeProbability(double, double)"><code>RealDistribution.cumulativeProbability(double,double)</code></a></i></div>
</div>
</td>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#density(double)">density</a></strong>(double&nbsp;x)</code>
<div class="block">Returns the probability density function (PDF) of this distribution
evaluated at the specified point <code>x</code>.</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/ParetoDistribution.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/ParetoDistribution.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>double</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#getScale()">getScale</a></strong>()</code>
<div class="block">Returns the scale parameter of this distribution.</div>
</td>
</tr>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#getShape()">getShape</a></strong>()</code>
<div class="block">Returns the shape parameter of this distribution.</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>protected double</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#getSolverAbsoluteAccuracy()">getSolverAbsoluteAccuracy</a></strong>()</code>
<div class="block">Returns the solver absolute accuracy for inverse cumulative computation.</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/ParetoDistribution.html#getSupportLowerBound()">getSupportLowerBound</a></strong>()</code>
<div class="block">Access the lower bound of the support.</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/ParetoDistribution.html#getSupportUpperBound()">getSupportUpperBound</a></strong>()</code>
<div class="block">Access the upper bound of the support.</div>
</td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>boolean</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.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="rowColor">
<td class="colFirst"><code>boolean</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#isSupportLowerBoundInclusive()">isSupportLowerBoundInclusive</a></strong>()</code>
<div class="block">Whether or not the lower bound of support is in the domain of the density
function.</div>
</td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>boolean</code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#isSupportUpperBoundInclusive()">isSupportUpperBoundInclusive</a></strong>()</code>
<div class="block">Whether or not the upper bound of support is in the domain of the density
function.</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/ParetoDistribution.html#logDensity(double)">logDensity</a></strong>(double&nbsp;x)</code>
<div class="block">Returns the natural logarithm of the probability density function (PDF) of this distribution
evaluated at the specified point <code>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/ParetoDistribution.html#sample()">sample</a></strong>()</code>
<div class="block">Generate a random value sampled from this distribution.</div>
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<code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#inverseCumulativeProbability(double)">inverseCumulativeProbability</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#probability(double)">probability</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#probability(double, double)">probability</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#reseedRandomGenerator(long)">reseedRandomGenerator</a>, <a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#sample(int)">sample</a></code></li>
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<pre>public static final&nbsp;double DEFAULT_INVERSE_ABSOLUTE_ACCURACY</pre>
<div class="block">Default inverse cumulative probability accuracy.</div>
<dl><dt><span class="strong">See Also:</span></dt><dd><a href="../../../../../constant-values.html#org.apache.commons.math3.distribution.ParetoDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY">Constant Field Values</a></dd></dl>
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<pre>public&nbsp;ParetoDistribution()</pre>
<div class="block">Create a Pareto distribution with a scale of <code>1</code> and a shape of <code>1</code>.</div>
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<pre>public&nbsp;ParetoDistribution(double&nbsp;scale,
double&nbsp;shape)
throws <a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></pre>
<div class="block">Create a Pareto distribution using the specified scale and shape.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>scale</code> - the scale parameter of this distribution</dd><dd><code>shape</code> - the shape parameter of this distribution</dd>
<dt><span class="strong">Throws:</span></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></code> - if <code>scale &lt;= 0</code> or <code>shape &lt;= 0</code>.</dd></dl>
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<pre>public&nbsp;ParetoDistribution(double&nbsp;scale,
double&nbsp;shape,
double&nbsp;inverseCumAccuracy)
throws <a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></pre>
<div class="block">Create a Pareto distribution using the specified scale, shape and
inverse cumulative distribution accuracy.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>scale</code> - the scale parameter of this distribution</dd><dd><code>shape</code> - the shape parameter of this distribution</dd><dd><code>inverseCumAccuracy</code> - Inverse cumulative probability accuracy.</dd>
<dt><span class="strong">Throws:</span></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></code> - if <code>scale &lt;= 0</code> or <code>shape &lt;= 0</code>.</dd></dl>
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<pre>public&nbsp;ParetoDistribution(<a href="../../../../../org/apache/commons/math3/random/RandomGenerator.html" title="interface in org.apache.commons.math3.random">RandomGenerator</a>&nbsp;rng,
double&nbsp;scale,
double&nbsp;shape)
throws <a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></pre>
<div class="block">Creates a log-normal distribution.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>rng</code> - Random number generator.</dd><dd><code>scale</code> - Scale parameter of this distribution.</dd><dd><code>shape</code> - Shape parameter of this distribution.</dd>
<dt><span class="strong">Throws:</span></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></code> - if <code>scale &lt;= 0</code> or <code>shape &lt;= 0</code>.</dd></dl>
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<pre>public&nbsp;ParetoDistribution(<a href="../../../../../org/apache/commons/math3/random/RandomGenerator.html" title="interface in org.apache.commons.math3.random">RandomGenerator</a>&nbsp;rng,
double&nbsp;scale,
double&nbsp;shape,
double&nbsp;inverseCumAccuracy)
throws <a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></pre>
<div class="block">Creates a log-normal distribution.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>rng</code> - Random number generator.</dd><dd><code>scale</code> - Scale parameter of this distribution.</dd><dd><code>shape</code> - Shape parameter of this distribution.</dd><dd><code>inverseCumAccuracy</code> - Inverse cumulative probability accuracy.</dd>
<dt><span class="strong">Throws:</span></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/exception/NotStrictlyPositiveException.html" title="class in org.apache.commons.math3.exception">NotStrictlyPositiveException</a></code> - if <code>scale &lt;= 0</code> or <code>shape &lt;= 0</code>.</dd></dl>
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</ul>
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<h3>Method Detail</h3>
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<h4>getScale</h4>
<pre>public&nbsp;double&nbsp;getScale()</pre>
<div class="block">Returns the scale parameter of this distribution.</div>
<dl><dt><span class="strong">Returns:</span></dt><dd>the scale parameter</dd></dl>
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<pre>public&nbsp;double&nbsp;getShape()</pre>
<div class="block">Returns the shape parameter of this distribution.</div>
<dl><dt><span class="strong">Returns:</span></dt><dd>the shape parameter</dd></dl>
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<a name="density(double)">
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<h4>density</h4>
<pre>public&nbsp;double&nbsp;density(double&nbsp;x)</pre>
<div class="block">Returns the probability density function (PDF) of this distribution
evaluated at the specified point <code>x</code>. In general, the PDF is
the derivative of the <a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html#cumulativeProbability(double)"><code>CDF</code></a>.
If the derivative does not exist at <code>x</code>, then an appropriate
replacement should be returned, e.g. <code>Double.POSITIVE_INFINITY</code>,
<code>Double.NaN</code>, or the limit inferior or limit superior of the
difference quotient.
<p>
For scale <code>k</code>, and shape <code>α</code> of this distribution, the PDF
is given by
<ul>
<li><code>0</code> if <code>x &lt; k</code>,</li>
<li><code>α * k^α / x^(α + 1)</code> otherwise.</li>
</ul></div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>x</code> - the point at which the PDF is evaluated</dd>
<dt><span class="strong">Returns:</span></dt><dd>the value of the probability density function at point <code>x</code></dd></dl>
</li>
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<pre>public&nbsp;double&nbsp;logDensity(double&nbsp;x)</pre>
<div class="block">Returns the natural logarithm of the probability density function (PDF) of this distribution
evaluated at the specified point <code>x</code>. In general, the PDF is the derivative of the
<a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html#cumulativeProbability(double)"><code>CDF</code></a>. If the derivative does not exist at <code>x</code>,
then an appropriate replacement should be returned, e.g. <code>Double.POSITIVE_INFINITY</code>,
<code>Double.NaN</code>, or the limit inferior or limit superior of the difference quotient. 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/RealDistribution.html#density(double)"><code>RealDistribution.density(double)</code></a>. The default implementation simply computes the logarithm of
<code>density(x)</code>.
See documentation of <a href="../../../../../org/apache/commons/math3/distribution/ParetoDistribution.html#density(double)"><code>density(double)</code></a> for computation details.</div>
<dl>
<dt><strong>Overrides:</strong></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#logDensity(double)">logDensity</a></code>&nbsp;in class&nbsp;<code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractRealDistribution</a></code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>x</code> - the point at which the PDF is evaluated</dd>
<dt><span class="strong">Returns:</span></dt><dd>the logarithm of the value of the probability density function at point <code>x</code></dd></dl>
</li>
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<pre>public&nbsp;double&nbsp;cumulativeProbability(double&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.
<p>
For scale <code>k</code>, and shape <code>α</code> of this distribution, the CDF is given by
<ul>
<li><code>0</code> if <code>x &lt; k</code>,</li>
<li><code>1 - (k / x)^α</code> otherwise.</li>
</ul></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>
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<h4>cumulativeProbability</h4>
<pre><a href="http://docs.oracle.com/javase/6/docs/api/java/lang/Deprecated.html?is-external=true" title="class or interface in java.lang">@Deprecated</a>
public&nbsp;double&nbsp;cumulativeProbability(double&nbsp;x0,
double&nbsp;x1)
throws <a href="../../../../../org/apache/commons/math3/exception/NumberIsTooLargeException.html" title="class in org.apache.commons.math3.exception">NumberIsTooLargeException</a></pre>
<div class="block"><span class="strong">Deprecated.</span>&nbsp;<i>See <a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html#cumulativeProbability(double, double)"><code>RealDistribution.cumulativeProbability(double,double)</code></a></i></div>
<div class="block">For a random variable <code>X</code> whose values are distributed according
to this distribution, this method returns <code>P(x0 &lt; X &lt;= x1)</code>.
The default implementation uses the identity
<p><code>P(x0 &lt; X &lt;= x1) = P(X &lt;= x1) - P(X &lt;= x0)</code></p></div>
<dl>
<dt><strong>Specified by:</strong></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html#cumulativeProbability(double, double)">cumulativeProbability</a></code>&nbsp;in interface&nbsp;<code><a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html" title="interface in org.apache.commons.math3.distribution">RealDistribution</a></code></dd>
<dt><strong>Overrides:</strong></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#cumulativeProbability(double, double)">cumulativeProbability</a></code>&nbsp;in class&nbsp;<code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractRealDistribution</a></code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>x0</code> - the exclusive lower bound</dd><dd><code>x1</code> - the inclusive upper bound</dd>
<dt><span class="strong">Returns:</span></dt><dd>the probability that a random variable with this distribution
takes a value between <code>x0</code> and <code>x1</code>,
excluding the lower and including the upper endpoint</dd>
<dt><span class="strong">Throws:</span></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/exception/NumberIsTooLargeException.html" title="class in org.apache.commons.math3.exception">NumberIsTooLargeException</a></code> - if <code>x0 &gt; x1</code></dd></dl>
</li>
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<pre>protected&nbsp;double&nbsp;getSolverAbsoluteAccuracy()</pre>
<div class="block">Returns the solver absolute accuracy for inverse cumulative computation.
You can override this method in order to use a Brent solver with an
absolute accuracy different from the default.</div>
<dl>
<dt><strong>Overrides:</strong></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#getSolverAbsoluteAccuracy()">getSolverAbsoluteAccuracy</a></code>&nbsp;in class&nbsp;<code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractRealDistribution</a></code></dd>
<dt><span class="strong">Returns:</span></dt><dd>the maximum absolute error in inverse cumulative probability estimates</dd></dl>
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<pre>public&nbsp;double&nbsp;getNumericalMean()</pre>
<div class="block">Use this method to get the numerical value of the mean of this
distribution.
<p>
For scale <code>k</code> and shape <code>α</code>, the mean is given by
<ul>
<li><code></code> if <code>α &lt;= 1</code>,</li>
<li><code>α * k / (α - 1)</code> otherwise.</li>
</ul></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.
<p>
For scale <code>k</code> and shape <code>α</code>, the variance is given by
<ul>
<li><code></code> if <code>1 &lt; α &lt;= 2</code>,</li>
<li><code>k^2 * α / ((α - 1)^2 * (α - 2))</code> otherwise.</li>
</ul></div>
<dl><dt><span class="strong">Returns:</span></dt><dd>the variance (possibly <code>Double.POSITIVE_INFINITY</code> as
for certain cases in <a href="../../../../../org/apache/commons/math3/distribution/TDistribution.html" title="class in org.apache.commons.math3.distribution"><code>TDistribution</code></a>) or <code>Double.NaN</code> if it
is not defined</dd></dl>
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<pre>public&nbsp;double&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 R | P(X <= x) > 0}</code>.</p>
<p>
The lower bound of the support is equal to the scale parameter <code>k</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;double&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>
<p>
The upper bound of the support is always positive infinity no matter the parameters.</div>
<dl><dt><span class="strong">Returns:</span></dt><dd>upper bound of the support (always <code>Double.POSITIVE_INFINITY</code>)</dd></dl>
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<pre>public&nbsp;boolean&nbsp;isSupportLowerBoundInclusive()</pre>
<div class="block">Whether or not the lower bound of support is in the domain of the density
function. Returns true iff <code>getSupporLowerBound()</code> is finite and
<code>density(getSupportLowerBound())</code> returns a non-NaN, non-infinite
value.</div>
<dl><dt><span class="strong">Returns:</span></dt><dd>true if the lower bound of support is finite and the density
function returns a non-NaN, non-infinite value there</dd></dl>
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<h4>isSupportUpperBoundInclusive</h4>
<pre>public&nbsp;boolean&nbsp;isSupportUpperBoundInclusive()</pre>
<div class="block">Whether or not the upper bound of support is in the domain of the density
function. Returns true iff <code>getSupportUpperBound()</code> is finite and
<code>density(getSupportUpperBound())</code> returns a non-NaN, non-infinite
value.</div>
<dl><dt><span class="strong">Returns:</span></dt><dd>true if the upper bound of support is finite and the density
function returns a non-NaN, non-infinite value there</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 values between the lower and upper bound of the support
are included in the support.
<p>
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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<h4>sample</h4>
<pre>public&nbsp;double&nbsp;sample()</pre>
<div class="block">Generate a random value sampled from this distribution.
The default implementation uses the
<a href="http://en.wikipedia.org/wiki/Inverse_transform_sampling">
inversion method.
</a></div>
<dl>
<dt><strong>Specified by:</strong></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html#sample()">sample</a></code>&nbsp;in interface&nbsp;<code><a href="../../../../../org/apache/commons/math3/distribution/RealDistribution.html" title="interface in org.apache.commons.math3.distribution">RealDistribution</a></code></dd>
<dt><strong>Overrides:</strong></dt>
<dd><code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html#sample()">sample</a></code>&nbsp;in class&nbsp;<code><a href="../../../../../org/apache/commons/math3/distribution/AbstractRealDistribution.html" title="class in org.apache.commons.math3.distribution">AbstractRealDistribution</a></code></dd>
<dt><span class="strong">Returns:</span></dt><dd>a random value.</dd></dl>
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