Math.NET Numerics
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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/StreamingStatistics.htm">StreamingStatistics</a>
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<div class="header">
<p class="class"><strong>Type</strong> RunningStatistics</p>
<p><strong>Namespace</strong> MathNet.Numerics.Statistics</p>
</div>
<div class="sub-header">
<div id="summary">Running statistics accumulator, allows updating by adding values
or by combining two accumulators. <blockquote class="remarks">
This type declares a DataContract for out of the box ephemeral serialization
with engines like DataContractSerializer, Protocol Buffers and FsPickler,
but does not guarantee any compatibility between versions.
It is not recommended to rely on this mechanism for durable persistence.
</blockquote>
</div>
<h3 class="section">Constructors</h3>
<ul>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#.ctor">RunningStatistics</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#.ctor">RunningStatistics</a></li>
</ul>
<h3 class="section">Static Functions</h3>
<ul>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Combine">Combine</a></li>
</ul>
<h3 class="section">Methods</h3>
<ul>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Equals">Equals</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#GetHashCode">GetHashCode</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#GetType">GetType</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Push">Push</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#PushRange">PushRange</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#ToString">ToString</a></li>
</ul>
<h3 class="section">Properties</h3>
<ul>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Count">Count</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Kurtosis">Kurtosis</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Maximum">Maximum</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Mean">Mean</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Minimum">Minimum</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#PopulationKurtosis">PopulationKurtosis</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#PopulationSkewness">PopulationSkewness</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#PopulationStandardDeviation">PopulationStandardDeviation</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#PopulationVariance">PopulationVariance</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Skewness">Skewness</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#StandardDeviation">StandardDeviation</a></li>
<li><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm#Variance">Variance</a></li>
</ul>
</div>
<h3 class="section">Public Constructors</h3>
<div id=".ctor" class="method">
<h4> <strong>RunningStatistics</strong>()</h4>
<div class="content">
</div>
</div>
<div id=".ctor" class="method">
<h4> <strong>RunningStatistics</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> values)</h4>
<div class="content">
</div>
</div>
<h3 class="section">Public Static Functions</h3>
<div id="Combine" class="method">
<h4><a href="../MathNet.Numerics.Statistics/RunningStatistics.htm">RunningStatistics</a> <strong>Combine</strong>(<a href="../MathNet.Numerics.Statistics/RunningStatistics.htm">RunningStatistics</a> a, <a href="../MathNet.Numerics.Statistics/RunningStatistics.htm">RunningStatistics</a> b)</h4>
<div class="content">Create a new running statistics over the combined samples of two existing running statistics.
</div>
</div>
<h3 class="section">Public Methods</h3>
<div id="Equals" class="method">
<h4><span title="System.bool">bool</span> <strong>Equals</strong>(<span title="System.object">object</span> obj)</h4>
<div class="content">
</div>
</div>
<div id="GetHashCode" class="method">
<h4><span title="System.int">int</span> <strong>GetHashCode</strong>()</h4>
<div class="content">
</div>
</div>
<div id="GetType" class="method">
<h4><span title="System.Type">Type</span> <strong>GetType</strong>()</h4>
<div class="content">
</div>
</div>
<div id="Push" class="method">
<h4><span title="System.void">void</span> <strong>Push</strong>(<span title="System.double">double</span> value)</h4>
<div class="content">Update the running statistics by adding another observed sample (in-place).
</div>
</div>
<div id="PushRange" class="method">
<h4><span title="System.void">void</span> <strong>PushRange</strong>(<span title="System.Collections.Generic.IEnumerable<double>">IEnumerable&lt;double&gt;</span> values)</h4>
<div class="content">Update the running statistics by adding a sequence of observed sample (in-place).
</div>
</div>
<div id="ToString" class="method">
<h4><span title="System.string">string</span> <strong>ToString</strong>()</h4>
<div class="content">
</div>
</div>
<h3 class="section">Public Properties</h3>
<div id="Count" class="method">
<h4><span title="System.long">long</span> <strong>Count</strong> get; </h4>
<div class="content">Gets the total number of samples.
</div>
</div>
<div id="Kurtosis" class="method">
<h4><span title="System.double">double</span> <strong>Kurtosis</strong> get; </h4>
<div class="content">Estimates the unbiased population kurtosis from the provided samples.
Uses a normalizer (Bessel's correction; type 2).
Returns NaN if data has less than four entries or if any entry is NaN.
</div>
</div>
<div id="Maximum" class="method">
<h4><span title="System.double">double</span> <strong>Maximum</strong> get; </h4>
<div class="content">Returns the maximum value in the sample data.
Returns NaN if data is empty or if any entry is NaN.
</div>
</div>
<div id="Mean" class="method">
<h4><span title="System.double">double</span> <strong>Mean</strong> get; </h4>
<div class="content">Evaluates the sample mean, an estimate of the population mean.
Returns NaN if data is empty or if any entry is NaN.
</div>
</div>
<div id="Minimum" class="method">
<h4><span title="System.double">double</span> <strong>Minimum</strong> get; </h4>
<div class="content">Returns the minimum value in the sample data.
Returns NaN if data is empty or if any entry is NaN.
</div>
</div>
<div id="PopulationKurtosis" class="method">
<h4><span title="System.double">double</span> <strong>PopulationKurtosis</strong> get; </h4>
<div class="content">Evaluates the population kurtosis from the full population.
Does not use a normalizer and would thus be biased if applied to a subset (type 1).
Returns NaN if data has less than three entries or if any entry is NaN.
</div>
</div>
<div id="PopulationSkewness" class="method">
<h4><span title="System.double">double</span> <strong>PopulationSkewness</strong> get; </h4>
<div class="content">Evaluates the population skewness from the full population.
Does not use a normalizer and would thus be biased if applied to a subset (type 1).
Returns NaN if data has less than two entries or if any entry is NaN.
</div>
</div>
<div id="PopulationStandardDeviation" class="method">
<h4><span title="System.double">double</span> <strong>PopulationStandardDeviation</strong> get; </h4>
<div class="content">Evaluates the standard deviation from the provided full population.
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>
</div>
<div id="PopulationVariance" class="method">
<h4><span title="System.double">double</span> <strong>PopulationVariance</strong> get; </h4>
<div class="content">Evaluates the variance from the provided full population.
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>
</div>
<div id="Skewness" class="method">
<h4><span title="System.double">double</span> <strong>Skewness</strong> get; </h4>
<div class="content">Estimates the unbiased population skewness from the provided samples.
Uses a normalizer (Bessel's correction; type 2).
Returns NaN if data has less than three entries or if any entry is NaN.
</div>
</div>
<div id="StandardDeviation" class="method">
<h4><span title="System.double">double</span> <strong>StandardDeviation</strong> get; </h4>
<div class="content">Estimates the unbiased population standard deviation from the provided samples.
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>
</div>
<div id="Variance" class="method">
<h4><span title="System.double">double</span> <strong>Variance</strong> get; </h4>
<div class="content">Estimates the unbiased population variance from the provided samples.
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>
</div>
<div id="footer">
<p>Based on v5.0.0.0 of MathNet.Numerics (Math.NET Numerics)</p>
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