OneSampleAndersonDarlingTest Class

Class OneSampleAndersonDarlingTest performs a Anderson-Darling test of the distribution of one sample.

Inheritance Hierarchy

SystemObject
CenterSpace.NMath.CoreOneSampleAndersonDarlingTest

Namespace: CenterSpace.NMath.Core
Assembly: NMath (in NMath.dll) Version: 7.4

Syntax

C++

Copy

[SerializableAttribute]
public class OneSampleAndersonDarlingTest : ICloneable

<SerializableAttribute>
Public Class OneSampleAndersonDarlingTest
	Implements ICloneable

[SerializableAttribute]
public ref class OneSampleAndersonDarlingTest : ICloneable

[<SerializableAttribute>]
type OneSampleAndersonDarlingTest = 
    class
        interface ICloneable
    end

The OneSampleAndersonDarlingTest type exposes the following members.

Constructors

	Name	Description
	OneSampleAndersonDarlingTest	Default constructor. Constructs an empty OneSampleAndersonDarlingTest instance.
	OneSampleAndersonDarlingTest(Double)	Constructs a OneSampleAndersonDarlingTest from the given sample data where the population mean and population standard deviation are unknown.
	OneSampleAndersonDarlingTest(DoubleVector)	Constructs a OneSampleAndersonDarlingTest from the given sample data where the population mean and population standard deviation are unknown.
	OneSampleAndersonDarlingTest(IDFColumn)	Constructs a OneSampleAndersonDarlingTest from the given sample data where the population mean and population standard deviation are unknown.
	OneSampleAndersonDarlingTest(Int32)	Constructs a OneSampleAndersonDarlingTest from the given sample data where the population mean and population standard deviation are unknown.
	OneSampleAndersonDarlingTest(Double, Double)	Constructs a OneSampleAndersonDarlingTest from the given sample data where the population mean and population standard deviation are unknown.
	OneSampleAndersonDarlingTest(DoubleVector, Double)	Constructs a OneSampleAndersonDarlingTest from the given sample data where the population mean and population standard deviation are unknown.
	OneSampleAndersonDarlingTest(IDFColumn, Double)	Constructs a OneSampleAndersonDarlingTest from the given sample data where the population mean and population standard deviation are unknown.
	OneSampleAndersonDarlingTest(Int32, Double)	Constructs a OneSampleAndersonDarlingTest from the given sample data where the population mean and population standard deviation are unknown.

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Properties

	Name	Description
	Alpha	Gets and sets the alpha level associated with this hypothesis test.
	DefaultAlpha	Default alpha level
	Error	Error message if the Anderson-Darling test fails on the provided data
	IsGood	If the test statistic cannot be derived then IsGood is set to false. Otherwise, IsGood is true.
	N	Gets the sample size.
	P	Gets the p-value associated with the test statistic.
	Reject	Tests whether the null hypothesis can be rejected using the current alpha level.
	S	Sample standard deviation.
	Statistic	Test statistic associated with this hypothesis test (A).
	StatisticStar	Modified Anderson Darling statistic used to derive P (A*)
	Xbar	Sample mean.

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Methods

	Name	Description
	Clone	Creates a deep copy of this OneSampleAndersonDarlingTest.
	ToString	Returns a formatted string representation of the test results. (Overrides ObjectToString)
	Update(Double)	Updates this test with new sample data.
	Update(DoubleVector)	Updates this test with the established parameters.
	Update(IDFColumn)	Updates this test with new sample data.
	Update(Int32)	Updates this test with new sample data.

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Remarks

Class OneSampleAndersonDarlingTest compares the distribution of a given sample to normal distribution function (CDF). The alternative hypothesis that the data do not have a normal distribution.

Reference

CenterSpace.NMath.Core Namespace