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527 lines
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527 lines
24 KiB
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<h2 class="fixed">Types in MathNet.Numerics.Statistics</h2>
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<a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm">ArrayStatistics</a>
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<a href="../MathNet.Numerics.Statistics/Bucket.htm">Bucket</a>
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<a href="../MathNet.Numerics.Statistics/Correlation.htm">Correlation</a>
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<a href="../MathNet.Numerics.Statistics/RunningStatistics.htm">RunningStatistics</a>
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<a href="../MathNet.Numerics.Statistics/SortedArrayStatistics.htm">SortedArrayStatistics</a>
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<a href="../MathNet.Numerics.Statistics/Statistics.htm">Statistics</a>
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<a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm" class="current">StreamingStatistics</a>
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</div>
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<div class="header">
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<p class="class"><strong>Type</strong> StreamingStatistics</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">Statistics operating on an IEnumerable in a single pass, without keeping the full data in memory.
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Can be used in a streaming way, e.g. on large datasets not fitting into memory.
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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/StreamingStatistics.htm#Covariance">Covariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#Entropy">Entropy</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#GeometricMean">GeometricMean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#HarmonicMean">HarmonicMean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#Maximum">Maximum</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#MaximumAbsolute">MaximumAbsolute</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#MaximumMagnitudePhase">MaximumMagnitudePhase</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#Mean">Mean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#MeanStandardDeviation">MeanStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#MeanVariance">MeanVariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#Minimum">Minimum</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#MinimumAbsolute">MinimumAbsolute</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#MinimumMagnitudePhase">MinimumMagnitudePhase</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#PopulationCovariance">PopulationCovariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#PopulationStandardDeviation">PopulationStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#PopulationVariance">PopulationVariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#RootMeanSquare">RootMeanSquare</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#StandardDeviation">StandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/StreamingStatistics.htm#Variance">Variance</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="Covariance" class="method">
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<h4><span title="System.double">double</span> <strong>Covariance</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> samples1, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> samples2)</h4>
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<div class="content">Estimates the unbiased population covariance from the provided two sample enumerable sequences, in a single pass without memoization.
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On a dataset of size N will use an N-1 normalizer (Bessel's correction).
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Returns NaN if data has less than two entries or if any entry is NaN.
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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> samples1</h6>
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<p class="comments">First sample stream. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> samples2</h6>
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<p class="comments">Second sample stream. </p>
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</div>
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</div>
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</div>
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<div id="Entropy" class="method">
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<h4><span title="System.double">double</span> <strong>Entropy</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
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<div class="content">Calculates the entropy of a stream of double values.
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Returns NaN if any of the values in the stream are NaN.
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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> stream</h6>
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<p class="comments">The input stream to evaluate. </p>
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</div>
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</div>
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</div>
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<div id="GeometricMean" class="method">
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<h4><span title="System.double">double</span> <strong>GeometricMean</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
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<div class="content">Evaluates the geometric mean of the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="HarmonicMean" class="method">
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<h4><span title="System.double">double</span> <strong>HarmonicMean</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
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<div class="content">Evaluates the harmonic mean of the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="Maximum" class="method">
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<h4><span title="System.double">double</span> <strong>Maximum</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
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<div class="content">Returns the largest value from the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="MaximumAbsolute" class="method">
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<h4><span title="System.double">double</span> <strong>MaximumAbsolute</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
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<div class="content">Returns the largest absolute value from the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="MaximumMagnitudePhase" class="method">
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<h4><span title="System.Numerics.Complex">Complex</span> <strong>MaximumMagnitudePhase</strong>(<span title="System.Collections.Generic.IEnumerable<Complex>">IEnumerable<Complex></span> stream)</h4>
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<div class="content">Returns the largest absolute value from the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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<Complex>">IEnumerable<Complex></span></code> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="Mean" class="method">
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<h4><span title="System.double">double</span> <strong>Mean</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
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<div class="content">Estimates the arithmetic sample mean from the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="MeanStandardDeviation" class="method">
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<h4><span title="System.ValueTuple<double, double>">ValueTuple<double, double></span> <strong>MeanStandardDeviation</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> samples)</h4>
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<div class="content">Estimates the arithmetic sample mean and the unbiased population standard deviation from the provided samples as enumerable sequence, in a single pass without memoization.
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On a dataset of size N will use an N-1 normalizer (Bessel's correction).
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Returns NaN for mean if data is empty or any entry is NaN, and NaN for standard deviation if data has less than two entries or if any entry is NaN.
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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> samples</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="MeanVariance" class="method">
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<h4><span title="System.ValueTuple<double, double>">ValueTuple<double, double></span> <strong>MeanVariance</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> samples)</h4>
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<div class="content">Estimates the arithmetic sample mean and the unbiased population variance from the provided samples as enumerable sequence, in a single pass without memoization.
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On a dataset of size N will use an N-1 normalizer (Bessel's correction).
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Returns NaN for mean if data is empty or any entry is NaN, and NaN for variance if data has less than two entries or if any entry is NaN.
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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> samples</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="Minimum" class="method">
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<h4><span title="System.double">double</span> <strong>Minimum</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
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<div class="content">Returns the smallest value from the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="MinimumAbsolute" class="method">
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<h4><span title="System.double">double</span> <strong>MinimumAbsolute</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
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<div class="content">Returns the smallest absolute value from the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="MinimumMagnitudePhase" class="method">
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<h4><span title="System.Numerics.Complex">Complex</span> <strong>MinimumMagnitudePhase</strong>(<span title="System.Collections.Generic.IEnumerable<Complex>">IEnumerable<Complex></span> stream)</h4>
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<div class="content">Returns the smallest absolute value from the enumerable, in a single pass without memoization.
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Returns NaN if data is empty or any entry is NaN.
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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<Complex>">IEnumerable<Complex></span></code> stream</h6>
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<p class="comments">Sample stream, no sorting is assumed. </p>
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</div>
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</div>
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</div>
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<div id="PopulationCovariance" class="method">
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<h4><span title="System.double">double</span> <strong>PopulationCovariance</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> population1, <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> population2)</h4>
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<div class="content">Evaluates the population covariance from the full population provided as two enumerable sequences, in a single pass without memoization.
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On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset.
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Returns NaN if data is empty or if any entry is NaN.
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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> population1</h6>
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<p class="comments">First population stream. </p>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> population2</h6>
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<p class="comments">Second population stream. </p>
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</div>
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</div>
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</div>
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<div id="PopulationStandardDeviation" class="method">
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<h4><span title="System.double">double</span> <strong>PopulationStandardDeviation</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> population)</h4>
|
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<div class="content">Evaluates the population standard deviation from the full population provided as enumerable sequence, in a single pass without memoization.
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On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset.
|
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Returns NaN if data is empty or if any entry is NaN.
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<div class="parameters">
|
|
<h5>Parameters</h5>
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<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> population</h6>
|
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<p class="comments">Sample stream, no sorting is assumed. </p>
|
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</div>
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</div>
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</div>
|
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<div id="PopulationVariance" class="method">
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|
<h4><span title="System.double">double</span> <strong>PopulationVariance</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> population)</h4>
|
|
<div class="content">Evaluates the population variance from the full population provided as enumerable sequence, in a single pass without memoization.
|
|
On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset.
|
|
Returns NaN if data is empty or if any entry is NaN.
|
|
|
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<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
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|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> population</h6>
|
|
<p class="comments">Sample stream, no sorting is assumed. </p>
|
|
</div>
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</div>
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</div>
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<div id="RootMeanSquare" class="method">
|
|
<h4><span title="System.double">double</span> <strong>RootMeanSquare</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> stream)</h4>
|
|
<div class="content">Estimates the root mean square (RMS) also known as quadratic mean from the enumerable, in a single pass without memoization.
|
|
Returns NaN if data is empty or any entry is NaN.
|
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|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> stream</h6>
|
|
<p class="comments">Sample stream, no sorting is assumed. </p>
|
|
</div>
|
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|
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</div>
|
|
</div>
|
|
<div id="StandardDeviation" class="method">
|
|
<h4><span title="System.double">double</span> <strong>StandardDeviation</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> samples)</h4>
|
|
<div class="content">Estimates the unbiased population standard deviation from the provided samples as enumerable sequence, in a single pass without memoization.
|
|
On a dataset of size N will use an N-1 normalizer (Bessel's correction).
|
|
Returns NaN if data has less than two entries or if any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> samples</h6>
|
|
<p class="comments">Sample stream, no sorting is assumed. </p>
|
|
</div>
|
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</div>
|
|
</div>
|
|
<div id="Variance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Variance</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> samples)</h4>
|
|
<div class="content">Estimates the unbiased population variance from the provided samples as enumerable sequence, in a single pass without memoization.
|
|
On a dataset of size N will use an N-1 normalizer (Bessel's correction).
|
|
Returns NaN if data has less than two entries or if any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span></code> samples</h6>
|
|
<p class="comments">Sample stream, no sorting is assumed. </p>
|
|
</div>
|
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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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