DescriptiveStatistics Class

Computes the basic statistics of data set. The class meets the NIST standard of accuracy for mean, variance, and standard deviation (the only statistics they provide exact values for) and exceeds them in increased accuracy mode.

Inheritance Hierarchy

SystemObject
MathNet.Numerics.StatisticsDescriptiveStatistics

Namespace: MathNet.Numerics.Statistics
Assembly: MathNet.Numerics (in MathNet.Numerics.dll) Version: 3.7

Syntax

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public class DescriptiveStatistics

The DescriptiveStatistics type exposes the following members.

Constructors

	Name	Description
	DescriptiveStatistics(IEnumerableDouble, Boolean)	Initializes a new instance of the DescriptiveStatistics class.
	DescriptiveStatistics(IEnumerableNullableDouble, Boolean)	Initializes a new instance of the DescriptiveStatistics class.

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Properties

	Name	Description
	Count	Gets the size of the sample.
	Kurtosis	Gets the sample kurtosis.
	Maximum	Gets the maximum sample value.
	Mean	Gets the sample mean.
	Minimum	Gets the minimum sample value.
	Skewness	Gets the sample skewness.
	StandardDeviation	Gets the unbiased population standard deviation (on a dataset of size N will use an N-1 normalizer).
	Variance	Gets the unbiased population variance estimator (on a dataset of size N will use an N-1 normalizer).

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Methods

	Name	Description
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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Remarks

Consider to use RunningStatistics instead.

Reference

MathNet.Numerics.Statistics Namespace