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1488 lines
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1488 lines
67 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" class="current">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/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">StreamingStatistics</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> ArrayStatistics</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 arrays assumed to be unsorted.
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WARNING: Methods with the Inplace-suffix may modify the data array by reordering its entries.
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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/ArrayStatistics.htm#Covariance">Covariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Covariance">Covariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Covariance">Covariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#FiveNumberSummaryInplace">FiveNumberSummaryInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#FiveNumberSummaryInplace">FiveNumberSummaryInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#GeometricMean">GeometricMean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#GeometricMean">GeometricMean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#GeometricMean">GeometricMean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#HarmonicMean">HarmonicMean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#HarmonicMean">HarmonicMean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#HarmonicMean">HarmonicMean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#InterquartileRangeInplace">InterquartileRangeInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#InterquartileRangeInplace">InterquartileRangeInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#LowerQuartileInplace">LowerQuartileInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#LowerQuartileInplace">LowerQuartileInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Maximum">Maximum</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Maximum">Maximum</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MaximumAbsolute">MaximumAbsolute</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MaximumAbsolute">MaximumAbsolute</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MaximumMagnitudePhase">MaximumMagnitudePhase</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MaximumMagnitudePhase">MaximumMagnitudePhase</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Mean">Mean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Mean">Mean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Mean">Mean</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MeanStandardDeviation">MeanStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MeanStandardDeviation">MeanStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MeanStandardDeviation">MeanStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MeanVariance">MeanVariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MeanVariance">MeanVariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MeanVariance">MeanVariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MedianInplace">MedianInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MedianInplace">MedianInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Minimum">Minimum</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Minimum">Minimum</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MinimumAbsolute">MinimumAbsolute</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MinimumAbsolute">MinimumAbsolute</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MinimumMagnitudePhase">MinimumMagnitudePhase</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#MinimumMagnitudePhase">MinimumMagnitudePhase</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#OrderStatisticInplace">OrderStatisticInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#OrderStatisticInplace">OrderStatisticInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PercentileInplace">PercentileInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PercentileInplace">PercentileInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationCovariance">PopulationCovariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationCovariance">PopulationCovariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationCovariance">PopulationCovariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationStandardDeviation">PopulationStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationStandardDeviation">PopulationStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationStandardDeviation">PopulationStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationVariance">PopulationVariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationVariance">PopulationVariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#PopulationVariance">PopulationVariance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#QuantileCustomInplace">QuantileCustomInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#QuantileCustomInplace">QuantileCustomInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#QuantileCustomInplace">QuantileCustomInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#QuantileCustomInplace">QuantileCustomInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#QuantileInplace">QuantileInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#QuantileInplace">QuantileInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#RanksInplace">RanksInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#RanksInplace">RanksInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#RootMeanSquare">RootMeanSquare</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#RootMeanSquare">RootMeanSquare</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#RootMeanSquare">RootMeanSquare</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#StandardDeviation">StandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#StandardDeviation">StandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#StandardDeviation">StandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#UpperQuartileInplace">UpperQuartileInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#UpperQuartileInplace">UpperQuartileInplace</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Variance">Variance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.htm#Variance">Variance</a></li>
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<li><a href="../MathNet.Numerics.Statistics/ArrayStatistics.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.Single[]">Single[]</span> samples1, <span title="System.Single[]">Single[]</span> samples2)</h4>
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<div class="content">Estimates the unbiased population covariance from the provided two sample arrays.
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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.Single[]">Single[]</span></code> samples1</h6>
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<p class="comments">First sample array. </p>
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<h6><code><span title="System.Single[]">Single[]</span></code> samples2</h6>
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<p class="comments">Second sample array. </p>
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</div>
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</div>
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</div>
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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.Int32[]">Int32[]</span> samples1, <span title="System.Int32[]">Int32[]</span> samples2)</h4>
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<div class="content">Estimates the unbiased population covariance from the provided two sample arrays.
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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.Int32[]">Int32[]</span></code> samples1</h6>
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<p class="comments">First sample array. </p>
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<h6><code><span title="System.Int32[]">Int32[]</span></code> samples2</h6>
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<p class="comments">Second sample array. </p>
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</div>
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</div>
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</div>
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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.Double[]">Double[]</span> samples1, <span title="System.Double[]">Double[]</span> samples2)</h4>
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<div class="content">Estimates the unbiased population covariance from the provided two sample arrays.
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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.Double[]">Double[]</span></code> samples1</h6>
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<p class="comments">First sample array. </p>
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<h6><code><span title="System.Double[]">Double[]</span></code> samples2</h6>
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<p class="comments">Second sample array. </p>
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</div>
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</div>
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</div>
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<div id="FiveNumberSummaryInplace" class="method">
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<h4><span title="System.Single[]">Single[]</span> <strong>FiveNumberSummaryInplace</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
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<div class="content">Estimates {min, lower-quantile, median, upper-quantile, max} from the unsorted data array.
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Approximately median-unbiased regardless of the sample distribution (R8).
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WARNING: Works inplace and can thus causes the data array to be reordered.
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<div class="parameters">
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<h5>Parameters</h5>
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<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
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<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
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</div>
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</div>
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</div>
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<div id="FiveNumberSummaryInplace" class="method">
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<h4><span title="System.Double[]">Double[]</span> <strong>FiveNumberSummaryInplace</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
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<div class="content">Estimates {min, lower-quantile, median, upper-quantile, max} from the unsorted data array.
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Approximately median-unbiased regardless of the sample distribution (R8).
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WARNING: Works inplace and can thus causes the data array to be reordered.
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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> data</h6>
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<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
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</div>
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|
|
</div>
|
|
</div>
|
|
<div id="GeometricMean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>GeometricMean</strong>(<span title="System.Int32[]">Int32[]</span> data)</h4>
|
|
<div class="content">Evaluates the geometric mean of the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="GeometricMean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>GeometricMean</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Evaluates the geometric mean of the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="GeometricMean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>GeometricMean</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Evaluates the geometric mean of the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="HarmonicMean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>HarmonicMean</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Evaluates the harmonic mean of the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="HarmonicMean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>HarmonicMean</strong>(<span title="System.Int32[]">Int32[]</span> data)</h4>
|
|
<div class="content">Evaluates the harmonic mean of the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="HarmonicMean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>HarmonicMean</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Evaluates the harmonic mean of the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="InterquartileRangeInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>InterquartileRangeInplace</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Estimates the inter-quartile range from the unsorted data array.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="InterquartileRangeInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>InterquartileRangeInplace</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Estimates the inter-quartile range from the unsorted data array.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="LowerQuartileInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>LowerQuartileInplace</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Estimates the first quartile value from the unsorted data array.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="LowerQuartileInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>LowerQuartileInplace</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Estimates the first quartile value from the unsorted data array.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Maximum" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Maximum</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Returns the largest value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Maximum" class="method">
|
|
<h4><span title="System.float">float</span> <strong>Maximum</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Returns the smallest value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MaximumAbsolute" class="method">
|
|
<h4><span title="System.double">double</span> <strong>MaximumAbsolute</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Returns the largest absolute value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MaximumAbsolute" class="method">
|
|
<h4><span title="System.float">float</span> <strong>MaximumAbsolute</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Returns the largest absolute value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MaximumMagnitudePhase" class="method">
|
|
<h4><span title="System.Numerics.Complex">Complex</span> <strong>MaximumMagnitudePhase</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> data)</h4>
|
|
<div class="content">Returns the largest absolute value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MaximumMagnitudePhase" class="method">
|
|
<h4><a href="../MathNet.Numerics/Complex32.htm">Complex32</a> <strong>MaximumMagnitudePhase</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> data)</h4>
|
|
<div class="content">Returns the largest absolute value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Mean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Mean</strong>(<span title="System.Int32[]">Int32[]</span> data)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Mean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Mean</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Mean" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Mean</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MeanStandardDeviation" class="method">
|
|
<h4><span title="System.ValueTuple<double, double>">ValueTuple<double, double></span> <strong>MeanStandardDeviation</strong>(<span title="System.Single[]">Single[]</span> samples)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean and the unbiased population standard deviation from the provided samples as unsorted array.
|
|
On a dataset of size N will use an N-1 normalizer (Bessel's correction).
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MeanStandardDeviation" class="method">
|
|
<h4><span title="System.ValueTuple<double, double>">ValueTuple<double, double></span> <strong>MeanStandardDeviation</strong>(<span title="System.Int32[]">Int32[]</span> samples)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean and the unbiased population standard deviation from the provided samples as unsorted array.
|
|
On a dataset of size N will use an N-1 normalizer (Bessel's correction).
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MeanStandardDeviation" class="method">
|
|
<h4><span title="System.ValueTuple<double, double>">ValueTuple<double, double></span> <strong>MeanStandardDeviation</strong>(<span title="System.Double[]">Double[]</span> samples)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean and the unbiased population standard deviation from the provided samples as unsorted array.
|
|
On a dataset of size N will use an N-1 normalizer (Bessel's correction).
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MeanVariance" class="method">
|
|
<h4><span title="System.ValueTuple<double, double>">ValueTuple<double, double></span> <strong>MeanVariance</strong>(<span title="System.Single[]">Single[]</span> samples)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean and the unbiased population variance from the provided samples as unsorted array.
|
|
On a dataset of size N will use an N-1 normalizer (Bessel's correction).
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MeanVariance" class="method">
|
|
<h4><span title="System.ValueTuple<double, double>">ValueTuple<double, double></span> <strong>MeanVariance</strong>(<span title="System.Double[]">Double[]</span> samples)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean and the unbiased population variance from the provided samples as unsorted array.
|
|
On a dataset of size N will use an N-1 normalizer (Bessel's correction).
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MeanVariance" class="method">
|
|
<h4><span title="System.ValueTuple<double, double>">ValueTuple<double, double></span> <strong>MeanVariance</strong>(<span title="System.Int32[]">Int32[]</span> samples)</h4>
|
|
<div class="content">Estimates the arithmetic sample mean and the unbiased population variance from the provided samples as unsorted array.
|
|
On a dataset of size N will use an N-1 normalizer (Bessel's correction).
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MedianInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>MedianInplace</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Estimates the median value from the unsorted data array.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MedianInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>MedianInplace</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Estimates the median value from the unsorted data array.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Minimum" class="method">
|
|
<h4><span title="System.float">float</span> <strong>Minimum</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Returns the smallest value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Minimum" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Minimum</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Returns the smallest value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MinimumAbsolute" class="method">
|
|
<h4><span title="System.double">double</span> <strong>MinimumAbsolute</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Returns the smallest absolute value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MinimumAbsolute" class="method">
|
|
<h4><span title="System.float">float</span> <strong>MinimumAbsolute</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Returns the smallest absolute value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MinimumMagnitudePhase" class="method">
|
|
<h4><span title="System.Numerics.Complex">Complex</span> <strong>MinimumMagnitudePhase</strong>(<span title="System.Numerics.Complex[]">Complex[]</span> data)</h4>
|
|
<div class="content">Returns the smallest absolute value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Numerics.Complex[]">Complex[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="MinimumMagnitudePhase" class="method">
|
|
<h4><a href="../MathNet.Numerics/Complex32.htm">Complex32</a> <strong>MinimumMagnitudePhase</strong>(<span title="MathNet.Numerics.Complex32[]">Complex32[]</span> data)</h4>
|
|
<div class="content">Returns the smallest absolute value from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="MathNet.Numerics.Complex32[]">Complex32[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="OrderStatisticInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>OrderStatisticInplace</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.int">int</span> order)</h4>
|
|
<div class="content">Returns the order statistic (order 1..N) from the unsorted data array.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.int">int</span></code> order</h6>
|
|
<p class="comments">One-based order of the statistic, must be between 1 and N (inclusive). </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="OrderStatisticInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>OrderStatisticInplace</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.int">int</span> order)</h4>
|
|
<div class="content">Returns the order statistic (order 1..N) from the unsorted data array.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.int">int</span></code> order</h6>
|
|
<p class="comments">One-based order of the statistic, must be between 1 and N (inclusive). </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PercentileInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>PercentileInplace</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.int">int</span> p)</h4>
|
|
<div class="content">Estimates the p-Percentile value from the unsorted data array.
|
|
If a non-integer Percentile is needed, use Quantile instead.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.int">int</span></code> p</h6>
|
|
<p class="comments">Percentile selector, between 0 and 100 (inclusive). </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PercentileInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PercentileInplace</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.int">int</span> p)</h4>
|
|
<div class="content">Estimates the p-Percentile value from the unsorted data array.
|
|
If a non-integer Percentile is needed, use Quantile instead.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.int">int</span></code> p</h6>
|
|
<p class="comments">Percentile selector, between 0 and 100 (inclusive). </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationCovariance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationCovariance</strong>(<span title="System.Int32[]">Int32[]</span> population1, <span title="System.Int32[]">Int32[]</span> population2)</h4>
|
|
<div class="content">Evaluates the population covariance from the full population provided as two arrays.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> population1</h6>
|
|
<p class="comments">First population array. </p>
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> population2</h6>
|
|
<p class="comments">Second population array. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationCovariance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationCovariance</strong>(<span title="System.Double[]">Double[]</span> population1, <span title="System.Double[]">Double[]</span> population2)</h4>
|
|
<div class="content">Evaluates the population covariance from the full population provided as two arrays.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> population1</h6>
|
|
<p class="comments">First population array. </p>
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> population2</h6>
|
|
<p class="comments">Second population array. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationCovariance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationCovariance</strong>(<span title="System.Single[]">Single[]</span> population1, <span title="System.Single[]">Single[]</span> population2)</h4>
|
|
<div class="content">Evaluates the population covariance from the full population provided as two arrays.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> population1</h6>
|
|
<p class="comments">First population array. </p>
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> population2</h6>
|
|
<p class="comments">Second population array. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationStandardDeviation" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationStandardDeviation</strong>(<span title="System.Double[]">Double[]</span> population)</h4>
|
|
<div class="content">Evaluates the population standard deviation from the full population provided as unsorted array.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> population</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationStandardDeviation" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationStandardDeviation</strong>(<span title="System.Single[]">Single[]</span> population)</h4>
|
|
<div class="content">Evaluates the population standard deviation from the full population provided as unsorted array.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> population</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationStandardDeviation" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationStandardDeviation</strong>(<span title="System.Int32[]">Int32[]</span> population)</h4>
|
|
<div class="content">Evaluates the population standard deviation from the full population provided as unsorted array.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> population</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationVariance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationVariance</strong>(<span title="System.Single[]">Single[]</span> population)</h4>
|
|
<div class="content">Evaluates the population variance from the full population provided as unsorted array.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> population</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationVariance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationVariance</strong>(<span title="System.Double[]">Double[]</span> population)</h4>
|
|
<div class="content">Evaluates the population variance from the full population provided as unsorted array.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> population</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="PopulationVariance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>PopulationVariance</strong>(<span title="System.Int32[]">Int32[]</span> population)</h4>
|
|
<div class="content">Evaluates the population variance from the full population provided as unsorted array.
|
|
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.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> population</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="QuantileCustomInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>QuantileCustomInplace</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.double">double</span> tau, <span title="System.double">double</span> a, <span title="System.double">double</span> b, <span title="System.double">double</span> c, <span title="System.double">double</span> d)</h4>
|
|
<div class="content">Estimates the tau-th quantile from the unsorted data array.
|
|
The tau-th quantile is the data value where the cumulative distribution
|
|
function crosses tau. The quantile definition can be specified
|
|
by 4 parameters a, b, c and d, consistent with Mathematica.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.double">double</span></code> tau</h6>
|
|
<p class="comments">Quantile selector, between 0.0 and 1.0 (inclusive) </p>
|
|
<h6><code><span title="System.double">double</span></code> a</h6>
|
|
<p class="comments">a-parameter </p>
|
|
<h6><code><span title="System.double">double</span></code> b</h6>
|
|
<p class="comments">b-parameter </p>
|
|
<h6><code><span title="System.double">double</span></code> c</h6>
|
|
<p class="comments">c-parameter </p>
|
|
<h6><code><span title="System.double">double</span></code> d</h6>
|
|
<p class="comments">d-parameter </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="QuantileCustomInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>QuantileCustomInplace</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.double">double</span> tau, <a href="../MathNet.Numerics.Statistics/QuantileDefinition.htm">QuantileDefinition</a> definition)</h4>
|
|
<div class="content">Estimates the tau-th quantile from the unsorted data array.
|
|
The tau-th quantile is the data value where the cumulative distribution
|
|
function crosses tau. The quantile definition can be specified to be compatible
|
|
with an existing system.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.double">double</span></code> tau</h6>
|
|
<p class="comments">Quantile selector, between 0.0 and 1.0 (inclusive) </p>
|
|
<h6><code><a href="../MathNet.Numerics.Statistics/QuantileDefinition.htm">QuantileDefinition</a></code> definition</h6>
|
|
<p class="comments">Quantile definition, to choose what product/definition it should be consistent with </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="QuantileCustomInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>QuantileCustomInplace</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.double">double</span> tau, <a href="../MathNet.Numerics.Statistics/QuantileDefinition.htm">QuantileDefinition</a> definition)</h4>
|
|
<div class="content">Estimates the tau-th quantile from the unsorted data array.
|
|
The tau-th quantile is the data value where the cumulative distribution
|
|
function crosses tau. The quantile definition can be specified to be compatible
|
|
with an existing system.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.double">double</span></code> tau</h6>
|
|
<p class="comments">Quantile selector, between 0.0 and 1.0 (inclusive) </p>
|
|
<h6><code><a href="../MathNet.Numerics.Statistics/QuantileDefinition.htm">QuantileDefinition</a></code> definition</h6>
|
|
<p class="comments">Quantile definition, to choose what product/definition it should be consistent with </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="QuantileCustomInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>QuantileCustomInplace</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.double">double</span> tau, <span title="System.double">double</span> a, <span title="System.double">double</span> b, <span title="System.double">double</span> c, <span title="System.double">double</span> d)</h4>
|
|
<div class="content">Estimates the tau-th quantile from the unsorted data array.
|
|
The tau-th quantile is the data value where the cumulative distribution
|
|
function crosses tau. The quantile definition can be specified
|
|
by 4 parameters a, b, c and d, consistent with Mathematica.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.double">double</span></code> tau</h6>
|
|
<p class="comments">Quantile selector, between 0.0 and 1.0 (inclusive) </p>
|
|
<h6><code><span title="System.double">double</span></code> a</h6>
|
|
<p class="comments">a-parameter </p>
|
|
<h6><code><span title="System.double">double</span></code> b</h6>
|
|
<p class="comments">b-parameter </p>
|
|
<h6><code><span title="System.double">double</span></code> c</h6>
|
|
<p class="comments">c-parameter </p>
|
|
<h6><code><span title="System.double">double</span></code> d</h6>
|
|
<p class="comments">d-parameter </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="QuantileInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>QuantileInplace</strong>(<span title="System.Single[]">Single[]</span> data, <span title="System.double">double</span> tau)</h4>
|
|
<div class="content">Estimates the tau-th quantile from the unsorted data array.
|
|
The tau-th quantile is the data value where the cumulative distribution
|
|
function crosses tau.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered. <blockquote class="remarks">
|
|
R-8, SciPy-(1/3,1/3):
|
|
Linear interpolation of the approximate medians for order statistics.
|
|
When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.double">double</span></code> tau</h6>
|
|
<p class="comments">Quantile selector, between 0.0 and 1.0 (inclusive). </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="QuantileInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>QuantileInplace</strong>(<span title="System.Double[]">Double[]</span> data, <span title="System.double">double</span> tau)</h4>
|
|
<div class="content">Estimates the tau-th quantile from the unsorted data array.
|
|
The tau-th quantile is the data value where the cumulative distribution
|
|
function crosses tau.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered. <blockquote class="remarks">
|
|
R-8, SciPy-(1/3,1/3):
|
|
Linear interpolation of the approximate medians for order statistics.
|
|
When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
|
|
</blockquote>
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
<h6><code><span title="System.double">double</span></code> tau</h6>
|
|
<p class="comments">Quantile selector, between 0.0 and 1.0 (inclusive). </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="RanksInplace" class="method">
|
|
<h4><span title="System.Single[]">Single[]</span> <strong>RanksInplace</strong>(<span title="System.Single[]">Single[]</span> data, <a href="../MathNet.Numerics.Statistics/RankDefinition.htm">RankDefinition</a> definition)</h4>
|
|
<div class="content">Evaluates the rank of each entry of the unsorted data array.
|
|
The rank definition can be specified to be compatible
|
|
with an existing system.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="RanksInplace" class="method">
|
|
<h4><span title="System.Double[]">Double[]</span> <strong>RanksInplace</strong>(<span title="System.Double[]">Double[]</span> data, <a href="../MathNet.Numerics.Statistics/RankDefinition.htm">RankDefinition</a> definition)</h4>
|
|
<div class="content">Evaluates the rank of each entry of the unsorted data array.
|
|
The rank definition can be specified to be compatible
|
|
with an existing system.
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="RootMeanSquare" class="method">
|
|
<h4><span title="System.double">double</span> <strong>RootMeanSquare</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Estimates the root mean square (RMS) also known as quadratic mean from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="RootMeanSquare" class="method">
|
|
<h4><span title="System.double">double</span> <strong>RootMeanSquare</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Estimates the root mean square (RMS) also known as quadratic mean from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="RootMeanSquare" class="method">
|
|
<h4><span title="System.double">double</span> <strong>RootMeanSquare</strong>(<span title="System.Int32[]">Int32[]</span> data)</h4>
|
|
<div class="content">Estimates the root mean square (RMS) also known as quadratic mean from the unsorted data array.
|
|
Returns NaN if data is empty or any entry is NaN.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Int32[]">Int32[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="StandardDeviation" class="method">
|
|
<h4><span title="System.double">double</span> <strong>StandardDeviation</strong>(<span title="System.Int32[]">Int32[]</span> samples)</h4>
|
|
<div class="content">Estimates the unbiased population standard deviation from the provided samples as unsorted array.
|
|
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.Int32[]">Int32[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="StandardDeviation" class="method">
|
|
<h4><span title="System.double">double</span> <strong>StandardDeviation</strong>(<span title="System.Single[]">Single[]</span> samples)</h4>
|
|
<div class="content">Estimates the unbiased population standard deviation from the provided samples as unsorted array.
|
|
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.Single[]">Single[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="StandardDeviation" class="method">
|
|
<h4><span title="System.double">double</span> <strong>StandardDeviation</strong>(<span title="System.Double[]">Double[]</span> samples)</h4>
|
|
<div class="content">Estimates the unbiased population standard deviation from the provided samples as unsorted array.
|
|
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.Double[]">Double[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="UpperQuartileInplace" class="method">
|
|
<h4><span title="System.double">double</span> <strong>UpperQuartileInplace</strong>(<span title="System.Double[]">Double[]</span> data)</h4>
|
|
<div class="content">Estimates the third quartile value from the unsorted data array.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Double[]">Double[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="UpperQuartileInplace" class="method">
|
|
<h4><span title="System.float">float</span> <strong>UpperQuartileInplace</strong>(<span title="System.Single[]">Single[]</span> data)</h4>
|
|
<div class="content">Estimates the third quartile value from the unsorted data array.
|
|
Approximately median-unbiased regardless of the sample distribution (R8).
|
|
WARNING: Works inplace and can thus causes the data array to be reordered.
|
|
|
|
|
|
<div class="parameters">
|
|
<h5>Parameters</h5>
|
|
|
|
<h6><code><span title="System.Single[]">Single[]</span></code> data</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. Will be reordered. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Variance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Variance</strong>(<span title="System.Single[]">Single[]</span> samples)</h4>
|
|
<div class="content">Estimates the unbiased population variance from the provided samples as unsorted array.
|
|
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.Single[]">Single[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Variance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Variance</strong>(<span title="System.Int32[]">Int32[]</span> samples)</h4>
|
|
<div class="content">Estimates the unbiased population variance from the provided samples as unsorted array.
|
|
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.Int32[]">Int32[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</div>
|
|
</div>
|
|
<div id="Variance" class="method">
|
|
<h4><span title="System.double">double</span> <strong>Variance</strong>(<span title="System.Double[]">Double[]</span> samples)</h4>
|
|
<div class="content">Estimates the unbiased population variance from the provided samples as unsorted array.
|
|
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.Double[]">Double[]</span></code> samples</h6>
|
|
<p class="comments">Sample array, no sorting is assumed. </p>
|
|
</div>
|
|
|
|
|
|
</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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|
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|
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