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.Tests
    • AndersonDarlingDistribution Class
    • AndersonDarlingTest Class
    • AnovaPostHocTest Class
    • BartlettTest Class
    • ChiSquareGoodnessOfFitTest Class
    • Exactness Enumeration
    • FTest Class
    • GeneralizedEsdTest Class
    • GrubbsTest Class
    • HypothesisTest Class
    • HypothesisType Enumeration
    • KruskalWallisTest Class
    • LeveneTest Class
    • LeveneTestLocationMeasure Enumeration
    • LjungBoxTest Class
    • MannWhitneyTest Class
    • MannWhitneyTest(T) Class
    • McNemarTest Class
    • MultiSampleTest Class
    • MultiSampleTest(T) Class
    • OneSampleChiSquareTest Class
    • OneSampleKolmogorovSmirnovTest Class
    • OneSampleTest Class
    • OneSampleTest(T) Class
    • OneSampleTTest Class
    • OneSampleZTest Class
    • OneSampleZTestOfProportion Class
    • RunsTest Class
    • RunsTest(T) Class
    • SamplePairing Enumeration
    • ShapiroWilkTest Class
    • SimpleHypothesisTest Class
    • StuartMaxwellTest Class
    • StudentizedRangeDistribution Class
    • TwoSampleKolmogorovSmirnovTest Class
    • TwoSampleTest Class
    • TwoSampleTest(T) Class
    • TwoSampleTTest Class
    • TwoSampleZTest Class
    • VarianceAssumption Enumeration
  • TwoSampleKolmogorovSmirnovTest Class
    • TwoSampleKolmogorovSmirnovTest Constructors
    • Properties
    • TwoSampleKolmogorovSmirnovTest Methods
TwoSampleKolmogorovSmirnovTest ClassExtreme Optimization Numerical Libraries for .NET Professional
Represents a test that two samples come from the same, unspecified distribution.
Inheritance Hierarchy
SystemObject
  Extreme.Statistics.TestsHypothesisTest
    Extreme.Statistics.TestsTwoSampleTestDouble
      Extreme.Statistics.TestsTwoSampleTest
        Extreme.Statistics.TestsTwoSampleKolmogorovSmirnovTest

Namespace: Extreme.Statistics.Tests
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 sealed class TwoSampleKolmogorovSmirnovTest : TwoSampleTest
Public NotInheritable Class TwoSampleKolmogorovSmirnovTest
	Inherits TwoSampleTest
public ref class TwoSampleKolmogorovSmirnovTest sealed : public TwoSampleTest
[<SealedAttribute>]
type TwoSampleKolmogorovSmirnovTest =  
    class
        inherit TwoSampleTest
    end

The TwoSampleKolmogorovSmirnovTest type exposes the following members.

Constructors
  NameDescription
Public methodTwoSampleKolmogorovSmirnovTest
Constructs a new Kolmogorov-Smirnov goodness-of-fit test for testing whether two samples come from the same (unknown) distribution.
Public methodTwoSampleKolmogorovSmirnovTest(NumericalVariable, NumericalVariable)
Constructs a new Kolmogorov-Smirnov goodness-of-fit test for testing whether two samples come from the same (unknown) distribution.
Public methodTwoSampleKolmogorovSmirnovTest(VectorDouble, VectorDouble)
Constructs a new Kolmogorov-Smirnov goodness-of-fit test for testing whether two samples come from the same (unknown) distribution.
Top
Properties
  NameDescription
Public propertyDistribution
Gets the probability distribution used in the hypothesis test.
(Inherited from HypothesisTest.)
Public propertyHypothesisType
Gets or sets whether the test is one or two-tailed.
(Inherited from HypothesisTest.)
Public propertyName
Gets the name of the hypothesis test.
(Overrides HypothesisTestName.)
Public propertyPValue
Gets the probability that the test statistic would take on the calculated value under the alternate hypothesis.
(Inherited from HypothesisTest.)
Public propertySample1
Gets or sets the first sample this test is being applied to.
(Inherited from TwoSampleTestT.)
Public propertySample2
Gets or sets the second sample this test is being applied to.
(Inherited from TwoSampleTestT.)
Public propertySignificanceLevel
Gets the significance level used to test the null hypothesis.
(Inherited from HypothesisTest.)
Public propertyStatistic
Gets the value of the test statistic.
(Inherited from HypothesisTest.)
Top
Methods
  NameDescription
Public methodEquals
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Public methodGetConfidenceInterval
Returns the confidence interval for the test parameter for the default confidence level.
(Inherited from HypothesisTest.)
Public methodGetConfidenceInterval(Double)
Returns the confidence interval for the test parameter for the specified confidence level.
(Inherited from HypothesisTest.)
Public methodGetHashCode
Serves as a hash function for a particular type.
(Inherited from Object.)
Public methodGetLowerCriticalValue
Gets the lower critical value for the hypothesis test's current significance level.
(Inherited from HypothesisTest.)
Public methodGetLowerCriticalValue(Double)
Gets the lower critical value for the hypothesis test at the specified significance level.
(Inherited from HypothesisTest.)
Public methodGetPValue
Gets the probability that the test statistic would take on the calculated value under the specified alternate hypothesis.
(Inherited from HypothesisTest.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodGetUpperCriticalValue
Gets the upper critical value for the test statistic at the hypothesis test's current significance level.
(Inherited from HypothesisTest.)
Public methodGetUpperCriticalValue(Double)
Gets the upper critical value for the test statistic at the specified significance level.
(Inherited from HypothesisTest.)
Public methodReject
Returns whether the null hypothesis is rejected using the default significance level.
(Inherited from HypothesisTest.)
Public methodReject(Double)
Returns whether the null hypothesis is rejected using the specified significance level.
(Inherited from HypothesisTest.)
Public methodSummarize
Returns a string containing a human-readable summary of the object.
(Inherited from HypothesisTest.)
Public methodSummarize(SummaryOptions)
Returns a string containing a human-readable summary of the object using the specified options.
(Inherited from HypothesisTest.)
Public methodToString
Returns a string that represents the current object.
(Inherited from HypothesisTest.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Top
Remarks

Use the TwoSampleKolmogorovSmirnovTest to test the hypothesis that two samples come from the same, unknown distribution.

The samples must be fully specified. The Sample1 and Sample2 properties must be set.

To test whether a sample comes

Version Information

Numerical Libraries

Supported in: 6.0, 5.x, 4.x
See Also

Reference

Extreme.Statistics.Tests Namespace

Copyright (c) 2004-2016 ExoAnalytics Inc.

Send comments on this topic to support@extremeoptimization.com

Copyright © 2004-20116, 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.