Extreme Optimization™: Complexity made simple.

Math and Statistics
Libraries for .NET

  • Home
  • Features
    • Math Library
    • Vector and Matrix Library
    • Statistics Library
    • Performance
    • Usability
  • Documentation
    • Introduction
    • Math Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Reference
  • Resources
    • Downloads
    • QuickStart Samples
    • Sample Applications
    • Frequently Asked Questions
    • Technical Support
  • Blog
  • Order
  • Company
    • About us
    • Testimonials
    • Customers
    • Press Releases
    • Careers
    • Partners
    • Contact us
Introduction
Deployment Guide
Configuration
Using Parallelism
Expand Mathematics Library User's GuideMathematics Library User's Guide
Expand Vector and Matrix Library User's GuideVector and Matrix Library User's Guide
Expand Data Analysis Library User's GuideData Analysis Library User's Guide
Expand Statistics Library User's GuideStatistics Library User's Guide
Expand Data Access Library User's GuideData Access Library User's Guide
Expand ReferenceReference
  • Extreme Optimization
    • Features
    • Solutions
    • Documentation
    • QuickStart Samples
    • Sample Applications
    • Downloads
    • Technical Support
    • Download trial
    • How to buy
    • Blog
    • Company
    • Resources
  • Documentation
    • Introduction
    • Deployment Guide
    • Configuration
    • Using Parallelism
    • Mathematics Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Data Access Library User's Guide
    • Reference
  • Reference
    • Extreme
    • Extreme.Collections
    • Extreme.Data
    • Extreme.Data.Json
    • Extreme.Data.Matlab
    • Extreme.Data.R
    • Extreme.Data.Stata
    • Extreme.Data.Text
    • Extreme.DataAnalysis
    • Extreme.DataAnalysis.Linq
    • Extreme.Mathematics
    • Extreme.Mathematics.Algorithms
    • Extreme.Mathematics.Calculus
    • Extreme.Mathematics.Calculus.OrdinaryDifferentialEquations
    • Extreme.Mathematics.Curves
    • Extreme.Mathematics.Curves.Nonlinear
    • Extreme.Mathematics.Distributed
    • Extreme.Mathematics.Distributed.Cuda
    • Extreme.Mathematics.EquationSolvers
    • Extreme.Mathematics.FSharp
    • Extreme.Mathematics.Generic
    • Extreme.Mathematics.Generic.LinearAlgebra
    • Extreme.Mathematics.Generic.LinearAlgebra.Implementation
    • Extreme.Mathematics.Generic.LinearAlgebra.Providers
    • Extreme.Mathematics.Generic.SignalProcessing
    • Extreme.Mathematics.Implementation
    • Extreme.Mathematics.LinearAlgebra
    • Extreme.Mathematics.LinearAlgebra.Complex
    • Extreme.Mathematics.LinearAlgebra.Complex.Decompositions
    • Extreme.Mathematics.LinearAlgebra.Implementation
    • Extreme.Mathematics.LinearAlgebra.IO
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers.Preconditioners
    • Extreme.Mathematics.LinearAlgebra.Providers
    • Extreme.Mathematics.LinearAlgebra.Sparse
    • Extreme.Mathematics.Optimization
    • Extreme.Mathematics.Optimization.Genetic
    • Extreme.Mathematics.Optimization.LineSearches
    • Extreme.Mathematics.Random
    • Extreme.Mathematics.SignalProcessing
    • Extreme.Numerics.FSharp
    • Extreme.Statistics
    • Extreme.Statistics.Distributions
    • Extreme.Statistics.IO
    • Extreme.Statistics.Linq
    • Extreme.Statistics.Multivariate
    • Extreme.Statistics.Random
    • Extreme.Statistics.Tests
    • Extreme.Statistics.TimeSeriesAnalysis
  • Extreme.Statistics
    • Aggregator Class
    • AnovaModel Class
    • AnovaModelRow Class
    • AnovaRow Class
    • AnovaRowCollection Class
    • AnovaRowType Enumeration
    • AnovaTable Class
    • BoundaryIntervalBehavior Enumeration
    • CategoricalScale Class
    • CategoricalVariable Class
    • CategoricalVariable.CategoricalFilters Structure
    • Cell Structure
    • CellArray Class
    • ClassificationModel Class
    • ClusteringModel Class
    • CollectionSortOrder Class
    • ContingencyTable Class
    • ContingencyTableCell Structure
    • DataArray(T) Class
    • DataArrayElement(T) Class
    • DateTimeInterval Structure
    • DateTimeScale Class
    • DateTimeUnit Enumeration
    • DateTimeVariable Class
    • DateTimeVariable.DateTimeFilters Structure
    • Descriptives(T) Class
    • Filter Class
    • GeneralizedLinearModel Class
    • Histogram Class
    • HistogramBin Structure
    • HistogramBinCollection Class
    • HypothesisTests Class
    • InsufficientDataException Class
    • ITransformationModel Interface
    • Kernel Class
    • KernelDensity Class
    • KernelDensityBandwidthEstimator Enumeration
    • KeyVariable Class
    • KeyVariable(T) Class
    • LinearRegressionModel Class
    • LinkFunction Class
    • LogisticRegressionMethod Enumeration
    • LogisticRegressionModel Class
    • MissingValueAction Enumeration
    • MissingValueException Class
    • Model Class
    • ModelExtensions Class
    • ModelFamily Class
    • ModelFitOptions Class
    • ModelInput Class
    • ModelInputCategory Enumeration
    • ModelInputFormat Enumeration
    • ModelInputGroup Class
    • ModelSerialization Enumeration
    • ModelStatus Enumeration
    • ModelTerm Class
    • ModelTermCollection Class
    • ModelTermKind Enumeration
    • MultipleMissingValueAction Enumeration
    • NearestCorrelationMatrixAlgorithm Enumeration
    • NonlinearRegressionModel Class
    • NumericalScale Class
    • NumericalVariable Class
    • NumericalVariable.NumericalFilters Structure
    • NumericalVariable.NumericalVariableTransforms Structure
    • Observation Structure
    • ObservationCollection Class
    • OneWayAnovaModel Class
    • OneWayRAnovaModel Class
    • Parameter Class
    • ParameterCollection Class
    • ParameterVector Class
    • PolynomialRegressionModel Class
    • RankTiebreaker Enumeration
    • RegressionModel Class
    • RegularizedRegressionModel Class
    • ScaleFittingMethod Enumeration
    • SeriesExtensions Class
    • SimpleRegressionKind Enumeration
    • SimpleRegressionModel Class
    • SortOrder Enumeration
    • SpecialBins Enumeration
    • Stats Class
    • StepwiseCriterion Enumeration
    • StepwiseOptions Class
    • StepwiseRegressionMethod Enumeration
    • SumsOfSquaresType Enumeration
    • TestOfHomogeneityOfVariances Enumeration
    • TestOfNormality Enumeration
    • TransformationModel Class
    • TransformedParameter Class
    • TwoWayAnovaModel Class
    • UnivariateModel Class
    • Variable Class
    • VariableCollection Class
    • WindowFilter Class
  • Stats Class
    • Methods
  • Methods
    • Autocorrelation Method Overloads
    • AverageAbsoluteDeviation Method
    • BlomScores Method Overloads
    • CentralMoment Method Overloads
    • CoefficientOfVariation Method
    • ColumnMeans Method Overloads
    • ColumnStandardDeviations Method Overloads
    • ColumnVariances Method Overloads
    • Correlation Method Overloads
    • CorrelationMatrix Method Overloads
    • Covariance Method Overloads
    • CovarianceMatrix Method Overloads
    • GeometricMean Method Overloads
    • GetKurtosisEstimate Method
    • GetMeanEstimate Method
    • GetSavitskyGolayCoefficients Method Overloads
    • GetSkewnessEstimate Method
    • GetStandardDeviationEstimate Method
    • HarmonicMean Method Overloads
    • InterQuartileRange Method Overloads
    • KendallTau Method Overloads
    • Kurtosis Method Overloads
    • Max Method Overloads
    • Mean Method Overloads
    • Median Method Overloads
    • MedianAbsoluteDeviation Method
    • MidMean Method
    • Min Method Overloads
    • MinMax Method Overloads
    • Moment Method Overloads
    • NearestCorrelationMatrix Method Overloads
    • Percentile Method Overloads
    • Percentiles Method Overloads
    • PopulationKurtosis Method Overloads
    • PopulationSkewness Method Overloads
    • PopulationStandardDeviation Method Overloads
    • PopulationVariance Method Overloads
    • ProcessMissingValues Method Overloads
    • Quantile Method Overloads
    • Quantiles Method Overloads
    • Range Method Overloads
    • RankCorrelation Method Overloads
    • Ranks Method Overloads
    • RootMeanSquare Method Overloads
    • RowMeans Method Overloads
    • RowStandardDeviations Method Overloads
    • RowVariances Method Overloads
    • Skewness Method Overloads
    • StandardDeviation Method Overloads
    • Sum Method Overloads
    • SumOfSquares Method Overloads
    • TrimmedMean Method Overloads
    • TukeyScores Method Overloads
    • VanDerWaerdenScores Method Overloads
    • Variance Method Overloads
    • WeightedMean Method Overloads
    • WeightedStandardDeviation Method Overloads
    • WinsorizedMean Method
  • Correlation Method Overloads
    • Correlation Method (Double[], Double[])
    • Correlation Method (NumericalVariable, NumericalVariable)
    • Correlation Method (Vector(Double), Vector(Double))
    • Correlation Method (Vector, Vector)
  • Correlation Method (Vector(Double), Vector(Double))
StatsCorrelation Method (VectorDouble, VectorDouble)Extreme Optimization Numerical Libraries for .NET Professional
Gets the Pearson correlation coefficient between two sets of values.

Namespace: Extreme.Statistics
Assembly: Extreme.Numerics.Net40 (in Extreme.Numerics.Net40.dll) Version: 6.0.16073.0 (6.0.16312.0)
Syntax

C#
VB
C++
F#
Copy
public static double Correlation(
	this Vector<double> data1,
	Vector<double> data2
)
<ExtensionAttribute>
Public Shared Function Correlation ( 
	data1 As Vector(Of Double),
	data2 As Vector(Of Double)
) As Double
public:
[ExtensionAttribute]
static double Correlation(
	Vector<double>^ data1, 
	Vector<double>^ data2
)
[<ExtensionAttribute>]
static member Correlation : 
        data1 : Vector<float> * 
        data2 : Vector<float> -> float 

Parameters

data1
Type: Extreme.MathematicsVectorDouble
A Double array.
data2
Type: Extreme.MathematicsVectorDouble
A Double array.

Return Value

Type: Double
The correlation between the two sets of values.

Usage Note

In Visual Basic and C#, you can call this method as an instance method on any object of type VectorDouble. When you use instance method syntax to call this method, omit the first parameter. For more information, see Extension Methods (Visual Basic) or Extension Methods (C# Programming Guide).
Exceptions

ExceptionCondition
ArgumentNullExceptiondata1 is .

-or-

data2 is .

DimensionMismatchException The length of data1 does not equal the length of data2.
Version Information

Numerical Libraries

Supported in: 6.0
See Also

Reference

Stats Class
Correlation Overload
Extreme.Statistics Namespace

Copyright (c) 2004-2016 ExoAnalytics Inc.

Send comments on this topic to support@extremeoptimization.com

Copyright © 2004-2018, Extreme Optimization. All rights reserved.
Extreme Optimization, Complexity made simple, M#, and M Sharp are trademarks of ExoAnalytics Inc.
Microsoft, Visual C#, Visual Basic, Visual Studio, Visual Studio.NET, and the Optimized for Visual Studio logo
are registered trademarks of Microsoft Corporation.