AndersonDarlingTest Constructor

public AndersonDarlingTest(
	Vector<double> sample
)

Public Sub New ( 
	sample As Vector(Of Double)
)

public:
AndersonDarlingTest(
	Vector<double>^ sample
)

new : 
        sample : Vector<float> -> AndersonDarlingTest

Parameters

sample  Vector<Double>

A vector.

The Anderson-Darling test works on any sample. The sample does not have to be normalized, for example.

public AndersonDarlingTest(
	Vector<double> sample,
	ContinuousDistribution distributionType
)

Public Sub New ( 
	sample As Vector(Of Double),
	distributionType As ContinuousDistribution
)

public:
AndersonDarlingTest(
	Vector<double>^ sample, 
	ContinuousDistribution^ distributionType
)

new : 
        sample : Vector<float> * 
        distributionType : ContinuousDistribution -> AndersonDarlingTest

Parameters

sample  Vector<Double>

A vector.

distributionType  ContinuousDistribution

The Type of the reference distribution.

The Anderson-Darling test works on any sample. The sample does not have to be normalized.

Some distributions have specialized equations for computing p-values: NormalDistribution, LognormalDistribution, ExponentialDistribution, GumbelDistribution (largest value only), LogisticDistribution.

Note that for these types of reference distributions, the test will return results that are different from an Anderson-Darling test created using the distribution's cumulative distribution function (CDF) directly. This is because the algorithm used to compute the p-values for the Anderson-Darling distribution is different.

For other distributions, the cumulative distribution function is fitted directly.

public AndersonDarlingTest(
	Vector<double> sample,
	Func<double, double> cdf
)

Public Sub New ( 
	sample As Vector(Of Double),
	cdf As Func(Of Double, Double)
)

public:
AndersonDarlingTest(
	Vector<double>^ sample, 
	Func<double, double>^ cdf
)

new : 
        sample : Vector<float> * 
        cdf : Func<float, float> -> AndersonDarlingTest

Parameters

sample  Vector<Double>

A vector.

cdf  Func<Double, Double>

A function that evaluates the cumulative distribution function (CD) of the reference distribution.

This algorithm is based on a method by Marsaglia for computing the distribution function of the Anderson-Darling statistic for a uniform distribution.

Note that for some types of reference distributions, this method will return results that are different from an Anderson-Darling test created using the specific distribution object instead of its distribution function.

public AndersonDarlingTest(
	Vector<double> sample,
	double mean,
	double standardDeviation
)

Public Sub New ( 
	sample As Vector(Of Double),
	mean As Double,
	standardDeviation As Double
)

public:
AndersonDarlingTest(
	Vector<double>^ sample, 
	double mean, 
	double standardDeviation
)

new : 
        sample : Vector<float> * 
        mean : float * 
        standardDeviation : float -> AndersonDarlingTest

Parameters

sample  Vector<Double>

A vector.

mean  Double

The mean of the normal distribution to test against.

standardDeviation  Double

The standard deviation of the normal distribution to test against.

Use this constructor to create an AndersonDarlingTest object that can be used to test whether a sample follows a specific normal distribution.

Reference