ChiSquareGoodnessOfFitTest Constructor

Definition

Namespace: Numerics.NET.Statistics.Tests
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.3

Overload List

ChiSquareGoodnessOfFitTest(Histogram<Double>, ContinuousDistribution)	Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.
ChiSquareGoodnessOfFitTest(Histogram<Int32>, DiscreteDistribution)	Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.
ChiSquareGoodnessOfFitTest(ICategoricalVector, Vector<Double>)	Constructs a new chi-squared goodness-of-fit test for the specified distribution.
ChiSquareGoodnessOfFitTest(Vector<Double>, Distribution)	Constructs a new chi-squared goodness-of-fit test for the specified distribution.
ChiSquareGoodnessOfFitTest(Vector<Double>, Vector<Double>)	Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.
ChiSquareGoodnessOfFitTest(Histogram<Double>, ContinuousDistribution, Int32)	Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.
ChiSquareGoodnessOfFitTest(Histogram<Int32>, DiscreteDistribution, Int32)	Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.
ChiSquareGoodnessOfFitTest(Vector<Double>, Distribution, Int32)	Constructs a new chi-squared goodness-of-fit test for the specified distribution.

ChiSquareGoodnessOfFitTest(Histogram<Double>, ContinuousDistribution)

Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.

public ChiSquareGoodnessOfFitTest(
	Histogram<double> histogram,
	ContinuousDistribution distribution
)

Visual Basic

Public Sub New ( 
	histogram As Histogram(Of Double),
	distribution As ContinuousDistribution
)

C++/CLI

public:
ChiSquareGoodnessOfFitTest(
	Histogram<double>^ histogram, 
	ContinuousDistribution^ distribution
)

new : 
        histogram : Histogram<float> * 
        distribution : ContinuousDistribution -> ChiSquareGoodnessOfFitTest

Parameters

histogram Histogram<Double>: A vector that specifies the sample data.
distribution ContinuousDistribution: A ContinuousDistribution object that represents the distribution that is to be compared.

Remarks

The test created by this constructor assumes that none of the parameters of distribution were estimated from the sample.

ChiSquareGoodnessOfFitTest(Histogram<Int32>, DiscreteDistribution)

Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.

public ChiSquareGoodnessOfFitTest(
	Histogram<int> histogram,
	DiscreteDistribution distribution
)

Visual Basic

Public Sub New ( 
	histogram As Histogram(Of Integer),
	distribution As DiscreteDistribution
)

C++/CLI

public:
ChiSquareGoodnessOfFitTest(
	Histogram<int>^ histogram, 
	DiscreteDistribution^ distribution
)

new : 
        histogram : Histogram<int> * 
        distribution : DiscreteDistribution -> ChiSquareGoodnessOfFitTest

Parameters

histogram Histogram<Int32>: A vector that specifies the sample data.
distribution DiscreteDistribution: A DiscreteDistribution object that represents the distribution that is to be compared.

Remarks

The test created by this constructor assumes that none of the parameters of distribution were estimated from the sample.

ChiSquareGoodnessOfFitTest(ICategoricalVector, Vector<Double>)

Constructs a new chi-squared goodness-of-fit test for the specified distribution.

public ChiSquareGoodnessOfFitTest(
	ICategoricalVector sample,
	Vector<double> expected
)

Visual Basic

Public Sub New ( 
	sample As ICategoricalVector,
	expected As Vector(Of Double)
)

C++/CLI

public:
ChiSquareGoodnessOfFitTest(
	ICategoricalVector^ sample, 
	Vector<double>^ expected
)

new : 
        sample : ICategoricalVector * 
        expected : Vector<float> -> ChiSquareGoodnessOfFitTest

Parameters

sample ICategoricalVector: A categorical vector that specifies the sample.
expected Vector<Double>: A vector that specifies the data expected from the proposed distribution.

ChiSquareGoodnessOfFitTest(Vector<Double>, Distribution)

Constructs a new chi-squared goodness-of-fit test for the specified distribution.

public ChiSquareGoodnessOfFitTest(
	Vector<double> sample,
	Distribution distribution
)

Visual Basic

Public Sub New ( 
	sample As Vector(Of Double),
	distribution As Distribution
)

C++/CLI

public:
ChiSquareGoodnessOfFitTest(
	Vector<double>^ sample, 
	Distribution^ distribution
)

new : 
        sample : Vector<float> * 
        distribution : Distribution -> ChiSquareGoodnessOfFitTest

Parameters

sample Vector<Double>: A vector that specifies the sample.
distribution Distribution: A Distribution object that represents the distribution that is to be compared.

Remarks

The test created by this constructor assumes that none of the parameters of distribution were estimated from the sample.

ChiSquareGoodnessOfFitTest(Vector<Double>, Vector<Double>)

Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.

public ChiSquareGoodnessOfFitTest(
	Vector<double> actual,
	Vector<double> expected
)

Visual Basic

Public Sub New ( 
	actual As Vector(Of Double),
	expected As Vector(Of Double)
)

C++/CLI

public:
ChiSquareGoodnessOfFitTest(
	Vector<double>^ actual, 
	Vector<double>^ expected
)

new : 
        actual : Vector<float> * 
        expected : Vector<float> -> ChiSquareGoodnessOfFitTest

Parameters

actual Vector<Double>: A vector that specifies the sample.
expected Vector<Double>: A vector that specifies the data expected from the proposed distribution.

Remarks

Both histograms must have the same bin boundaries.

ChiSquareGoodnessOfFitTest(Histogram<Double>, ContinuousDistribution, Int32)

Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.

public ChiSquareGoodnessOfFitTest(
	Histogram<double> histogram,
	ContinuousDistribution distribution,
	int numberOfEstimatedParameters
)

Visual Basic

Public Sub New ( 
	histogram As Histogram(Of Double),
	distribution As ContinuousDistribution,
	numberOfEstimatedParameters As Integer
)

C++/CLI

public:
ChiSquareGoodnessOfFitTest(
	Histogram<double>^ histogram, 
	ContinuousDistribution^ distribution, 
	int numberOfEstimatedParameters
)

new : 
        histogram : Histogram<float> * 
        distribution : ContinuousDistribution * 
        numberOfEstimatedParameters : int -> ChiSquareGoodnessOfFitTest

Parameters

histogram Histogram<Double>: A vector that specifies the sample data.
distribution ContinuousDistribution: A ContinuousDistribution object that represents the distribution that is to be compared.
numberOfEstimatedParameters Int32: The number of parameters of distribution that were estimated from the sample.

Remarks

The reason the number of estimated parameters is important, is that it decreases the number of degrees of freedom of the sample relative to the distribution.

ChiSquareGoodnessOfFitTest(Histogram<Int32>, DiscreteDistribution, Int32)

Constructs a new chi-squared goodness-of-fit test for the specified distribution using histogram data.

public ChiSquareGoodnessOfFitTest(
	Histogram<int> histogram,
	DiscreteDistribution distribution,
	int numberOfEstimatedParameters
)

Visual Basic

Public Sub New ( 
	histogram As Histogram(Of Integer),
	distribution As DiscreteDistribution,
	numberOfEstimatedParameters As Integer
)

C++/CLI

public:
ChiSquareGoodnessOfFitTest(
	Histogram<int>^ histogram, 
	DiscreteDistribution^ distribution, 
	int numberOfEstimatedParameters
)

new : 
        histogram : Histogram<int> * 
        distribution : DiscreteDistribution * 
        numberOfEstimatedParameters : int -> ChiSquareGoodnessOfFitTest

Parameters

histogram Histogram<Int32>: A vector that specifies the sample data.
distribution DiscreteDistribution: A ContinuousDistribution object that represents the distribution that is to be compared.
numberOfEstimatedParameters Int32: The number of parameters of distribution that were estimated from the sample.

Remarks

The reason the number of estimated parameters is important, is that it decreases the number of degrees of freedom of the sample relative to the distribution.

ChiSquareGoodnessOfFitTest(Vector<Double>, Distribution, Int32)

Constructs a new chi-squared goodness-of-fit test for the specified distribution.

public ChiSquareGoodnessOfFitTest(
	Vector<double> sample,
	Distribution distribution,
	int numberOfEstimatedParameters
)

Visual Basic

Public Sub New ( 
	sample As Vector(Of Double),
	distribution As Distribution,
	numberOfEstimatedParameters As Integer
)

C++/CLI

public:
ChiSquareGoodnessOfFitTest(
	Vector<double>^ sample, 
	Distribution^ distribution, 
	int numberOfEstimatedParameters
)

new : 
        sample : Vector<float> * 
        distribution : Distribution * 
        numberOfEstimatedParameters : int -> ChiSquareGoodnessOfFitTest

Parameters

sample Vector<Double>: A vector that specifies the sample.
distribution Distribution: A ContinuousDistribution object that represents the distribution that is to be compared.
numberOfEstimatedParameters Int32: The number of parameters of distribution that were estimated from the sample sample.

Remarks

The reason the number of estimated parameters is important, is that it decreases the number of degrees of freedom of the sample relative to the distribution.

ChiSquareGoodnessOfFitTest Constructor

Definition

Overload List

ChiSquareGoodnessOfFitTest(Histogram<Double>, ContinuousDistribution)

Parameters

Remarks

ChiSquareGoodnessOfFitTest(Histogram<Int32>, DiscreteDistribution)

Parameters

Remarks

ChiSquareGoodnessOfFitTest(ICategoricalVector, Vector<Double>)

Parameters

ChiSquareGoodnessOfFitTest(Vector<Double>, Distribution)

Parameters

Remarks

ChiSquareGoodnessOfFitTest(Vector<Double>, Vector<Double>)

Parameters

Remarks

ChiSquareGoodnessOfFitTest(Histogram<Double>, ContinuousDistribution, Int32)

Parameters

Remarks

ChiSquareGoodnessOfFitTest(Histogram<Int32>, DiscreteDistribution, Int32)

Parameters

Remarks

ChiSquareGoodnessOfFitTest(Vector<Double>, Distribution, Int32)

Parameters

Remarks

See Also

Reference