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393 lines
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393 lines
17 KiB
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<a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm">ArrayStatistics</a>
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<a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm">StreamingStatistics</a>
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<div class="header">
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<p class="class"><strong>Type</strong> Correlation</p>
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<p><strong>Namespace</strong> MathNet.Numerics.Statistics</p>
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</div>
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<div class="sub-header">
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<div id="summary">A class with correlation measures between two datasets.
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</div>
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<h3 class="section">Static Functions</h3>
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<ul>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#Auto">Auto</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#Auto">Auto</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#Auto">Auto</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#Pearson">Pearson</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#PearsonMatrix">PearsonMatrix</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#PearsonMatrix">PearsonMatrix</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#Spearman">Spearman</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#SpearmanMatrix">SpearmanMatrix</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#SpearmanMatrix">SpearmanMatrix</a></li>
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<li><a href="../MathNet.Numerics.Statistics/Correlation.htm#WeightedPearson">WeightedPearson</a></li>
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</ul>
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</div>
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<h3 class="section">Public Static Functions</h3>
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<div id="Auto" class="method">
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<h4><span title="System.Double[]">Double[]</span> <strong>Auto</strong>(<span title="System.Double[]">Double[]</span> x)</h4>
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<div class="content">Auto-correlation function (ACF) based on FFT for all possible lags k.
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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">Data array to calculate auto correlation for. </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>An array with the ACF as a function of the lags k. </p>
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</div>
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</div>
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</div>
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<div id="Auto" class="method">
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<h4><span title="System.Double[]">Double[]</span> <strong>Auto</strong>(<span title="System.Double[]">Double[]</span> x, <span title="System.int">int</span> kMax, <span title="System.int">int</span> kMin)</h4>
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<div class="content">Auto-correlation function (ACF) based on FFT for lags between kMin and kMax.
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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 data array to calculate auto correlation for. </p>
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<h6><code><span title="System.int">int</span></code> kMax</h6>
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<p class="comments">Max lag to calculate ACF for must be positive and smaller than x.Length. </p>
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<h6><code><span title="System.int">int</span></code> kMin</h6>
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<p class="comments">Min lag to calculate ACF for (0 = no shift with acf=1) must be zero or positive and smaller than x.Length. </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>An array with the ACF as a function of the lags k. </p>
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</div>
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</div>
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</div>
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<div id="Auto" class="method">
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<h4><span title="System.Double[]">Double[]</span> <strong>Auto</strong>(<span title="System.Double[]">Double[]</span> x, <span title="System.Int32[]">Int32[]</span> k)</h4>
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<div class="content">Auto-correlation function based on FFT for lags k.
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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 data array to calculate auto correlation for. </p>
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<h6><code><span title="System.Int32[]">Int32[]</span></code> k</h6>
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<p class="comments">Array with lags to calculate ACF for. </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>An array with the ACF as a function of the lags k. </p>
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</div>
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</div>
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</div>
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<div id="Pearson" class="method">
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<h4><span title="System.double">double</span> <strong>Pearson</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> dataA, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> dataB)</h4>
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<div class="content">Computes the Pearson Product-Moment Correlation coefficient.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> dataA</h6>
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<p class="comments">Sample data A. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> dataB</h6>
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<p class="comments">Sample data B. </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 Pearson product-moment correlation coefficient. </p>
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</div>
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</div>
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</div>
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<div id="PearsonMatrix" class="method">
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<h4><a href="../MathNet.Numerics.LinearAlgebra/Matrix`1.htm">Matrix<T></a> <strong>PearsonMatrix</strong>(<span title="System.Double[][]">Double[][]</span> vectors)</h4>
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<div class="content">
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</div>
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</div>
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<div id="PearsonMatrix" class="method">
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<h4><a href="../MathNet.Numerics.LinearAlgebra/Matrix`1.htm">Matrix<T></a> <strong>PearsonMatrix</strong>(<span title="System.Collections.Generic.IEnumerable<Double[]>">IEnumerable<Double[]></span> vectors)</h4>
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<div class="content">Computes the Pearson Product-Moment Correlation matrix.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<Double[]>">IEnumerable<Double[]></span></code> vectors</h6>
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<p class="comments">Enumerable of sample data vectors. </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><a href="../MathNet.Numerics.LinearAlgebra/Matrix`1.htm">Matrix<T></a></code></h6>
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<p>The Pearson product-moment correlation matrix. </p>
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</div>
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</div>
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</div>
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<div id="Spearman" class="method">
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<h4><span title="System.double">double</span> <strong>Spearman</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> dataA, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> dataB)</h4>
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<div class="content">Computes the Spearman Ranked Correlation coefficient.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> dataA</h6>
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<p class="comments">Sample data series A. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> dataB</h6>
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<p class="comments">Sample data series B. </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 Spearman ranked correlation coefficient. </p>
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</div>
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</div>
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</div>
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<div id="SpearmanMatrix" class="method">
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<h4><a href="../MathNet.Numerics.LinearAlgebra/Matrix`1.htm">Matrix<T></a> <strong>SpearmanMatrix</strong>(<span title="System.Double[][]">Double[][]</span> vectors)</h4>
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<div class="content">
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</div>
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</div>
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<div id="SpearmanMatrix" class="method">
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<h4><a href="../MathNet.Numerics.LinearAlgebra/Matrix`1.htm">Matrix<T></a> <strong>SpearmanMatrix</strong>(<span title="System.Collections.Generic.IEnumerable<Double[]>">IEnumerable<Double[]></span> vectors)</h4>
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<div class="content">Computes the Spearman Ranked Correlation matrix.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<Double[]>">IEnumerable<Double[]></span></code> vectors</h6>
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<p class="comments">Enumerable of sample data vectors. </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><a href="../MathNet.Numerics.LinearAlgebra/Matrix`1.htm">Matrix<T></a></code></h6>
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<p>The Spearman ranked correlation matrix. </p>
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</div>
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</div>
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</div>
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<div id="WeightedPearson" class="method">
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<h4><span title="System.double">double</span> <strong>WeightedPearson</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> dataA, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> dataB, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> weights)</h4>
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<div class="content">Computes the Weighted Pearson Product-Moment Correlation coefficient.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> dataA</h6>
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<p class="comments">Sample data A. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> dataB</h6>
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<p class="comments">Sample data B. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> weights</h6>
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<p class="comments">Corresponding weights of data. </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 Weighted Pearson product-moment correlation coefficient. </p>
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</div>
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</div>
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<div id="footer">
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<p>Based on v5.0.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
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<p>Generated by <a href="http://docu.jagregory.com">docu</a></p>
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