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1006 lines
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<a href="../MathNet.Numerics.Distributions/Bernoulli.htm">Bernoulli</a>
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<a href="../MathNet.Numerics.Distributions/Triangular.htm">Triangular</a>
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<a href="../MathNet.Numerics.Distributions/TruncatedPareto.htm">TruncatedPareto</a>
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</div>
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</div>
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<div class="header">
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<p class="class"><strong>Type</strong> Logistic</p>
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<p><strong>Namespace</strong> MathNet.Numerics.Distributions</p>
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<p><strong>Interfaces</strong> <a href="../MathNet.Numerics.Distributions/IContinuousDistribution.htm">IContinuousDistribution</a></p>
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</div>
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<div class="sub-header">
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<div id="summary">Continuous Univariate Logistic distribution.
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For details about this distribution, see.
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</div>
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<h3 class="section">Constructors</h3>
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<ul>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#.ctor">Logistic</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#.ctor">Logistic</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#.ctor">Logistic</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#.ctor">Logistic</a></li>
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</ul>
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<h3 class="section">Static Functions</h3>
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<ul>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#CDF">CDF</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#InvCDF">InvCDF</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#IsValidParameterSet">IsValidParameterSet</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#PDF">PDF</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#PDFLn">PDFLn</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Sample">Sample</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Sample">Sample</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Samples">Samples</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Samples">Samples</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Samples">Samples</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Samples">Samples</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#WithMeanPrecision">WithMeanPrecision</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#WithMeanScale">WithMeanScale</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#WithMeanStdDev">WithMeanStdDev</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#WithMeanVariance">WithMeanVariance</a></li>
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</ul>
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<h3 class="section">Methods</h3>
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<ul>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#CumulativeDistribution">CumulativeDistribution</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Density">Density</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#DensityLn">DensityLn</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Equals">Equals</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#GetHashCode">GetHashCode</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#GetType">GetType</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#InverseCumulativeDistribution">InverseCumulativeDistribution</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Sample">Sample</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Samples">Samples</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Samples">Samples</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#ToString">ToString</a></li>
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</ul>
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<h3 class="section">Properties</h3>
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<ul>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Entropy">Entropy</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Maximum">Maximum</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Mean">Mean</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Median">Median</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Minimum">Minimum</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Mode">Mode</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Precision">Precision</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#RandomSource">RandomSource</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Scale">Scale</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Skewness">Skewness</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#StdDev">StdDev</a></li>
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<li><a href="../MathNet.Numerics.Distributions/Logistic.htm#Variance">Variance</a></li>
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</ul>
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</div>
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<h3 class="section">Public Constructors</h3>
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<div id=".ctor" class="method">
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<h4> <strong>Logistic</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale, <span title="System.Random">Random</span> randomSource)</h4>
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<div class="content">Initializes a new instance of the Logistic class with a particular mean and standard deviation. The distribution will
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be initialized with the default random number generator.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.double">double</span></code> mean</h6>
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<p class="comments">The mean (μ) of the logistic distribution. </p>
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<h6><code><span title="System.double">double</span></code> scale</h6>
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<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
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<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
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<p class="comments">The random number generator which is used to draw random samples. </p>
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</div>
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</div>
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</div>
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<div id=".ctor" class="method">
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<h4> <strong>Logistic</strong>(<span title="System.Random">Random</span> randomSource)</h4>
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<div class="content">Initializes a new instance of the Logistic class. This is a logistic distribution with mean 0.0
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and scale 1.0. The distribution will be initialized with the default random number generator.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
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<p class="comments">The random number generator which is used to draw random samples. </p>
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</div>
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</div>
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</div>
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<div id=".ctor" class="method">
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<h4> <strong>Logistic</strong>()</h4>
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<div class="content">Initializes a new instance of the Logistic class. This is a logistic distribution with mean 0.0
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and scale 1.0. The distribution will be initialized with the default random number generator.
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</div>
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</div>
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<div id=".ctor" class="method">
|
|
<h4> <strong>Logistic</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale)</h4>
|
|
<div class="content">Initializes a new instance of the Logistic class with a particular mean and scale parameter. The
|
|
distribution will be initialized with the default random number generator.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
</div>
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|
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|
|
|
</div>
|
|
</div>
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|
<h3 class="section">Public Static Functions</h3>
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|
<div id="CDF" class="method">
|
|
<h4><span title="System.double">double</span> <strong>CDF</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale, <span title="System.double">double</span> x)</h4>
|
|
<div class="content">Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). <blockquote class="remarks">
|
|
MATLAB: normcdf
|
|
</blockquote>
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|
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|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
<h6><code><span title="System.double">double</span></code> x</h6>
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|
<p class="comments">The location at which to compute the cumulative distribution function. </p>
|
|
</div>
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|
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|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>the cumulative distribution at location <var>x</var>. </p>
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|
</div>
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|
</div>
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|
</div>
|
|
<div id="InvCDF" class="method">
|
|
<h4><span title="System.double">double</span> <strong>InvCDF</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale, <span title="System.double">double</span> p)</h4>
|
|
<div class="content">Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
|
|
at the given probability. This is also known as the quantile or percent point function. <blockquote class="remarks">
|
|
MATLAB: norminv
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|
</blockquote>
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|
|
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|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
<h6><code><span title="System.double">double</span></code> p</h6>
|
|
<p class="comments">The location at which to compute the inverse cumulative density. </p>
|
|
</div>
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|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>the inverse cumulative density at <var>p</var>. </p>
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|
</div>
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|
</div>
|
|
</div>
|
|
<div id="IsValidParameterSet" class="method">
|
|
<h4><span title="System.bool">bool</span> <strong>IsValidParameterSet</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale)</h4>
|
|
<div class="content">Tests whether the provided values are valid parameters for this distribution.
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|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PDF" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PDF</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale, <span title="System.double">double</span> x)</h4>
|
|
<div class="content">Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
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|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
<h6><code><span title="System.double">double</span></code> x</h6>
|
|
<p class="comments">The location at which to compute the density. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>the density at <var>x</var>. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PDFLn" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PDFLn</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale, <span title="System.double">double</span> x)</h4>
|
|
<div class="content">Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
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|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
<h6><code><span title="System.double">double</span></code> x</h6>
|
|
<p class="comments">The location at which to compute the density. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>the log density at <var>x</var>. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Sample" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Sample</strong>(<span title="System.Random">Random</span> rnd, <span title="System.double">double</span> mean, <span title="System.double">double</span> scale)</h4>
|
|
<div class="content">Generates a sample from the logistic distribution using the algorithm.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
|
|
<p class="comments">The random number generator to use. </p>
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>a sample from the distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Sample" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Sample</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale)</h4>
|
|
<div class="content">Generates a sample from the logistic distribution using the algorithm.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>a sample from the distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Samples" class="method">
|
|
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> <strong>Samples</strong>(<span title="System.Random">Random</span> rnd, <span title="System.double">double</span> mean, <span title="System.double">double</span> scale)</h4>
|
|
<div class="content">Generates a sequence of samples from the logistic distribution using the algorithm.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
|
|
<p class="comments">The random number generator to use. </p>
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code></h6>
|
|
<p>a sequence of samples from the distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Samples" class="method">
|
|
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Random">Random</span> rnd, <span title="System.Double[]">Double[]</span> values, <span title="System.double">double</span> mean, <span title="System.double">double</span> scale)</h4>
|
|
<div class="content">Fills an array with samples generated from the distribution.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Random">Random</span></code> rnd</h6>
|
|
<p class="comments">The random number generator to use. </p>
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> values</h6>
|
|
<p class="comments">The array to fill with the samples. </p>
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.void">void</span></code></h6>
|
|
<p>a sequence of samples from the distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Samples" class="method">
|
|
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> <strong>Samples</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale)</h4>
|
|
<div class="content">Generates a sequence of samples from the logistic distribution using the algorithm.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code></h6>
|
|
<p>a sequence of samples from the distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Samples" class="method">
|
|
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Double[]">Double[]</span> values, <span title="System.double">double</span> mean, <span title="System.double">double</span> scale)</h4>
|
|
<div class="content">Fills an array with samples generated from the distribution.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> values</h6>
|
|
<p class="comments">The array to fill with the samples. </p>
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.void">void</span></code></h6>
|
|
<p>a sequence of samples from the distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="WithMeanPrecision" class="method">
|
|
<h4><a href="../MathNet.Numerics.Distributions/Logistic.htm">Logistic</a> <strong>WithMeanPrecision</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> precision, <span title="System.Random">Random</span> randomSource)</h4>
|
|
<div class="content">Constructs a logistic distribution from a mean and precision.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> precision</h6>
|
|
<p class="comments">The precision of the logistic distribution. Range: precision > 0. </p>
|
|
<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
|
|
<p class="comments">The random number generator which is used to draw random samples. Optional, can be null. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Distributions/Logistic.htm">Logistic</a></code></h6>
|
|
<p>A logistic distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="WithMeanScale" class="method">
|
|
<h4><a href="../MathNet.Numerics.Distributions/Logistic.htm">Logistic</a> <strong>WithMeanScale</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> scale, <span title="System.Random">Random</span> randomSource)</h4>
|
|
<div class="content">Constructs a logistic distribution from a mean and scale parameter.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> scale</h6>
|
|
<p class="comments">The scale (s) of the logistic distribution. Range: s > 0. </p>
|
|
<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
|
|
<p class="comments">The random number generator which is used to draw random samples. Optional, can be null. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Distributions/Logistic.htm">Logistic</a></code></h6>
|
|
<p>a logistic distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="WithMeanStdDev" class="method">
|
|
<h4><a href="../MathNet.Numerics.Distributions/Logistic.htm">Logistic</a> <strong>WithMeanStdDev</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> stddev, <span title="System.Random">Random</span> randomSource)</h4>
|
|
<div class="content">Constructs a logistic distribution from a mean and standard deviation.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> stddev</h6>
|
|
<p class="comments">The standard deviation (σ) of the logistic distribution. Range: σ > 0. </p>
|
|
<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
|
|
<p class="comments">The random number generator which is used to draw random samples. Optional, can be null. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Distributions/Logistic.htm">Logistic</a></code></h6>
|
|
<p>a logistic distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="WithMeanVariance" class="method">
|
|
<h4><a href="../MathNet.Numerics.Distributions/Logistic.htm">Logistic</a> <strong>WithMeanVariance</strong>(<span title="System.double">double</span> mean, <span title="System.double">double</span> var, <span title="System.Random">Random</span> randomSource)</h4>
|
|
<div class="content">Constructs a logistic distribution from a mean and variance.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> mean</h6>
|
|
<p class="comments">The mean (μ) of the logistic distribution. </p>
|
|
<h6><code><span title="System.double">double</span></code> var</h6>
|
|
<p class="comments">The variance (σ^2) of the logistic distribution. Range: (σ^2) > 0. </p>
|
|
<h6><code><span title="System.Random">Random</span></code> randomSource</h6>
|
|
<p class="comments">The random number generator which is used to draw random samples. Optional, can be null. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><a href="../MathNet.Numerics.Distributions/Logistic.htm">Logistic</a></code></h6>
|
|
<p>A logistic distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
|
|
<h3 class="section">Public Methods</h3>
|
|
|
|
<div id="CumulativeDistribution" class="method">
|
|
<h4><span title="System.double">double</span> <strong>CumulativeDistribution</strong>(<span title="System.double">double</span> x)</h4>
|
|
<div class="content">Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.double">double</span></code> x</h6>
|
|
<p class="comments">The location at which to compute the cumulative distribution function. </p>
|
|
</div>
|
|
|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>the cumulative distribution at location <var>x</var>. </p>
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</div>
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</div>
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</div>
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<div id="Density" class="method">
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<h4><span title="System.double">double</span> <strong>Density</strong>(<span title="System.double">double</span> x)</h4>
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<div class="content">Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.double">double</span></code> x</h6>
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<p class="comments">The location at which to compute the density. </p>
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</div>
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<div class="return">
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<h5>Return</h5>
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<h6><code><span title="System.double">double</span></code></h6>
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<p>the density at <var>x</var>. </p>
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</div>
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</div>
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</div>
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<div id="DensityLn" class="method">
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<h4><span title="System.double">double</span> <strong>DensityLn</strong>(<span title="System.double">double</span> x)</h4>
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<div class="content">Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.double">double</span></code> x</h6>
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<p class="comments">The location at which to compute the log density. </p>
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</div>
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<div class="return">
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<h5>Return</h5>
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<h6><code><span title="System.double">double</span></code></h6>
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<p>the log density at <var>x</var>. </p>
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</div>
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</div>
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</div>
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<div id="Equals" class="method">
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<h4><span title="System.bool">bool</span> <strong>Equals</strong>(<span title="System.object">object</span> obj)</h4>
|
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<div class="content">
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</div>
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</div>
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<div id="GetHashCode" class="method">
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|
<h4><span title="System.int">int</span> <strong>GetHashCode</strong>()</h4>
|
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<div class="content">
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</div>
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</div>
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<div id="GetType" class="method">
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|
<h4><span title="System.Type">Type</span> <strong>GetType</strong>()</h4>
|
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<div class="content">
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</div>
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</div>
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|
<div id="InverseCumulativeDistribution" class="method">
|
|
<h4><span title="System.double">double</span> <strong>InverseCumulativeDistribution</strong>(<span title="System.double">double</span> p)</h4>
|
|
<div class="content">Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
|
|
at the given probability. This is also known as the quantile or percent point function.
|
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|
<div class="parameters">
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|
<h5>Parameters</h5>
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|
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<h6><code><span title="System.double">double</span></code> p</h6>
|
|
<p class="comments">The location at which to compute the inverse cumulative density. </p>
|
|
</div>
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|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>the inverse cumulative density at <var>p</var>. </p>
|
|
</div>
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|
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</div>
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|
</div>
|
|
<div id="Sample" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Sample</strong>()</h4>
|
|
<div class="content">Generates a sample from the logistic distribution using the algorithm.
|
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|
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<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.double">double</span></code></h6>
|
|
<p>a sample from the distribution. </p>
|
|
</div>
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|
|
|
</div>
|
|
</div>
|
|
<div id="Samples" class="method">
|
|
<h4><span title="System.void">void</span> <strong>Samples</strong>(<span title="System.Double[]">Double[]</span> values)</h4>
|
|
<div class="content">Fills an array with samples generated from the distribution.
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</div>
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</div>
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|
<div id="Samples" class="method">
|
|
<h4><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> <strong>Samples</strong>()</h4>
|
|
<div class="content">Generates a sequence of samples from the logistic distribution using the algorithm.
|
|
|
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<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code></h6>
|
|
<p>a sequence of samples from the distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
<div id="ToString" class="method">
|
|
<h4><span title="System.string">string</span> <strong>ToString</strong>()</h4>
|
|
<div class="content">A string representation of the distribution.
|
|
|
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|
|
<div class="return">
|
|
<h5>Return</h5>
|
|
<h6><code><span title="System.string">string</span></code></h6>
|
|
<p>a string representation of the distribution. </p>
|
|
</div>
|
|
|
|
</div>
|
|
</div>
|
|
|
|
<h3 class="section">Public Properties</h3>
|
|
|
|
<div id="Entropy" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Entropy</strong> get; </h4>
|
|
<div class="content">Gets the entropy of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Maximum" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Maximum</strong> get; </h4>
|
|
<div class="content">Gets the maximum of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Mean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Mean</strong> get; </h4>
|
|
<div class="content">Gets the mean (μ) of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Median" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Median</strong> get; </h4>
|
|
<div class="content">Gets the median of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Minimum" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Minimum</strong> get; </h4>
|
|
<div class="content">Gets the minimum of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Mode" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Mode</strong> get; </h4>
|
|
<div class="content">Gets the mode of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Precision" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Precision</strong> get; </h4>
|
|
<div class="content">Gets the precision of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="RandomSource" class="method">
|
|
<h4><span title="System.Random">Random</span> <strong>RandomSource</strong> get; set;</h4>
|
|
<div class="content">Gets the random number generator which is used to draw random samples.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Scale" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Scale</strong> get; </h4>
|
|
<div class="content">Gets the scale parameter of the Logistic distribution. Range: s > 0.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Skewness" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Skewness</strong> get; </h4>
|
|
<div class="content">Gets the skewness of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="StdDev" class="method">
|
|
<h4><span title="System.double">double</span> <strong>StdDev</strong> get; </h4>
|
|
<div class="content">Gets the standard deviation (σ) of the logistic distribution. Range: σ > 0.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Variance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Variance</strong> get; </h4>
|
|
<div class="content">Gets the variance of the logistic distribution.
|
|
|
|
</div>
|
|
</div>
|
|
<div id="footer">
|
|
<p>Based on v5.0.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
|
|
<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
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