BivariateSample Class

Represents a set of data points, where each data point is described by a pair of real numbers.

Inheritance Hierarchy

SystemObject
Meta.Numerics.StatisticsBivariateSample

Namespace: Meta.Numerics.Statistics
Assembly: Meta.Numerics (in Meta.Numerics.dll) Version: 4.1.4

Syntax

C++

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public sealed class BivariateSample : ICollection<XY>, 
	IEnumerable<XY>, IEnumerable

Public NotInheritable Class BivariateSample
	Implements ICollection(Of XY), IEnumerable(Of XY), 
	IEnumerable

public ref class BivariateSample sealed : ICollection<XY>, 
	IEnumerable<XY>, IEnumerable

[<SealedAttribute>]
type BivariateSample =  
    class
        interface ICollection<XY>
        interface IEnumerable<XY>
        interface IEnumerable
    end

The BivariateSample type exposes the following members.

Constructors

	Name	Description
	BivariateSample	Initializes a new bivariate sample.
	BivariateSample(String, String)	Initializes a new bivariate sample with the given variable names.

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Properties

	Name	Description
	CorrelationCoefficient	Gets the correlation coefficient between the two variables.
	Count	Gets the number of data points.
	Covariance	Gets the covariance of the two variables.
	IsReadOnly	Gets a value indicating whether the bivariate sample is read-only.
	PopulationCovariance	Estimates of the population covariance of two variables.
	X	Gets a read-only univariate sample consisting of the x-values of the data points.
	Y	Gets a read-only univariate sample consisting of the y-values of the data points.

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Methods

	Name	Description
	Add(XY)	Adds a data point to the sample.
	Add(IEnumerableXY)	Adds multiple data points to the sample.
	Add(IReadOnlyListDouble, IReadOnlyListDouble)	Adds points from two lists to the sample.
	Add(Double, Double)	Adds a data point to the sample.
	Clear	Removes all data points from the sample.
	Contains(XY)	Determines whether the sample contains a given data point.
	Contains(Double, Double)	Determines whether the sample contains a given data point.
	Copy	Copies the bivariate sample.
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	GetEnumerator	Gets an enumerator of sample values.
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	KendallTauTest	Performs a Kendall concordance test for association.
	LinearLogisticRegression	Computes the best-fit linear logistic regression from the data.
	LinearRegression	Computes the best-fit linear regression from the data.
	NonlinearRegression	Finds the parameterized function that best fits the data.
	PairedStudentTTest	Performs a paired Student t-test.
	PearsonRTest	Performs a Pearson correlation test for association.
	PolynomialRegression	Computes the polynomial of given degree which best fits the data.
	Remove(XY)	Removes a data point from the sample.
	Remove(Double, Double)	Removes a data point from the sample.
	SpearmanRhoTest	Performs a Spearman rank-order test of association between the two variables.
	ToString	Returns a string that represents the current object. (Inherited from Object.)
	TransposeXY	Swaps the X and Y variables in the bivariate sample.
	WilcoxonSignedRankTest	Performs a Wilcoxon signed rank test.

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Remarks

A bivariate sample consists of pairs of real numbers, where each pair is an independent measurement. For example, if you measure the height and weight of a sample of people, the data could be stored as a bivariate sample. The class can compute various descriptive statistics for the sample, perform appropriate statistical tests on the sample data, and fit the sample data to various models.

Reference

Meta.Numerics.Statistics Namespace