ChiSquareGoodnessOfFitTest Constructor

Definition

Namespace: Numerics.NET.Statistics.Tests
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.4

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

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

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

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

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.
C# 
public ChiSquareGoodnessOfFitTest(
	Vector<double> actual,
	Vector<double> expected
)

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

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

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

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.

See Also