BivariateSample Class

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

Definition

Namespace: Meta.Numerics.Statistics
Assembly: Meta.Numerics (in Meta.Numerics.dll) Version: 4.2.0+6d77d64445f7d5d91b12e331399c4362ecb25333
C#
public sealed class BivariateSample : ICollection<XY>, 
	IEnumerable<XY>, IEnumerable
Inheritance
Object    BivariateSample
Implements
ICollectionXY, IEnumerableXY, IEnumerable

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.

NOTE: This class will be retired in a future release. Its functionality is replaced by the Bivariate class, which can operatate on arbitrary data lists.

Constructors

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

Properties

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.

Methods

Add(IEnumerableXY) Adds multiple data points to the sample.
Add(XY) Adds a data point to the sample.
Add(Double, Double) Adds a data point to the sample.
Add(IReadOnlyListDouble, IReadOnlyListDouble) Adds points from two lists 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.
EqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object)
GetEnumerator Gets an enumerator of sample values.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetTypeGets 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.
ToStringReturns 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.

See Also