Wishart Class

Infer.NET Documentation

Microsoft Research, Cambridge

A Wishart distribution on positive definite matrices.

Inheritance Hierarchy

System�Object
��MicrosoftResearch.Infer.Distributions�Wishart

Namespace:�MicrosoftResearch.Infer.Distributions
Assembly:�Infer.Runtime (in Infer.Runtime.dll) Version: 2.5.30417.0 (2.5.30417.0)

Syntax

C++

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[SerializableAttribute]
[Quality(QualityBand.Mature)]
public�class�Wishart : IDistribution<PositiveDefiniteMatrix>, 
	ICloneable, HasPoint<PositiveDefiniteMatrix>, CanGetLogProb<PositiveDefiniteMatrix>, 
	SettableTo<Wishart>, SettableToProduct<Wishart>, SettableToProduct<Wishart, Wishart>, 
	Diffable, SettableToUniform, Sampleable<PositiveDefiniteMatrix>, SettableToRatio<Wishart>, 
	SettableToRatio<Wishart, Wishart>, SettableToPower<Wishart>, 
	CanGetMean<PositiveDefiniteMatrix>, CanGetVariance<PositiveDefiniteMatrix>, CanGetMeanAndVariance<PositiveDefiniteMatrix, PositiveDefiniteMatrix>, 
	CanSetMeanAndVariance<PositiveDefiniteMatrix, PositiveDefiniteMatrix>, CanGetLogAverageOf<Wishart>, 
	CanGetLogAverageOfPower<Wishart>, SettableToWeightedSum<Wishart>, CanGetAverageLog<Wishart>, 
	CanGetLogNormalizer

[SerializableAttribute]
[Quality(QualityBand.Mature)]
public�class�Wishart : IDistribution<PositiveDefiniteMatrix>, 
	ICloneable, HasPoint<PositiveDefiniteMatrix>, CanGetLogProb<PositiveDefiniteMatrix>, 
	SettableTo<Wishart>, SettableToProduct<Wishart>, SettableToProduct<Wishart, Wishart>, 
	Diffable, SettableToUniform, Sampleable<PositiveDefiniteMatrix>, SettableToRatio<Wishart>, 
	SettableToRatio<Wishart, Wishart>, SettableToPower<Wishart>, 
	CanGetMean<PositiveDefiniteMatrix>, CanGetVariance<PositiveDefiniteMatrix>, CanGetMeanAndVariance<PositiveDefiniteMatrix, PositiveDefiniteMatrix>, 
	CanSetMeanAndVariance<PositiveDefiniteMatrix, PositiveDefiniteMatrix>, CanGetLogAverageOf<Wishart>, 
	CanGetLogAverageOfPower<Wishart>, SettableToWeightedSum<Wishart>, CanGetAverageLog<Wishart>, 
	CanGetLogNormalizer

[<SerializableAttribute>]
[<Quality(QualityBand.Mature)>]
type�Wishart =  
    class�
��������interface�IDistribution<PositiveDefiniteMatrix>
        interface�ICloneable�
��������interface�HasPoint<PositiveDefiniteMatrix>
        interface�CanGetLogProb<PositiveDefiniteMatrix>
        interface�SettableTo<Wishart>
        interface�SettableToProduct<Wishart>
        interface�SettableToProduct<Wishart, Wishart>
        interface�Diffable�
��������interface�SettableToUniform�
��������interface�Sampleable<PositiveDefiniteMatrix>
        interface�SettableToRatio<Wishart>
        interface�SettableToRatio<Wishart, Wishart>
        interface�SettableToPower<Wishart>
        interface�CanGetMean<PositiveDefiniteMatrix>
        interface�CanGetVariance<PositiveDefiniteMatrix>
        interface�CanGetMeanAndVariance<PositiveDefiniteMatrix, PositiveDefiniteMatrix>
        interface�CanSetMeanAndVariance<PositiveDefiniteMatrix, PositiveDefiniteMatrix>
        interface�CanGetLogAverageOf<Wishart>
        interface�CanGetLogAverageOfPower<Wishart>
        interface�SettableToWeightedSum<Wishart>
        interface�CanGetAverageLog<Wishart>
        interface�CanGetLogNormalizer�
����end

[<SerializableAttribute>]
[<Quality(QualityBand.Mature)>]
type�Wishart =  
    class�
��������interface�IDistribution<PositiveDefiniteMatrix>
        interface�ICloneable�
��������interface�HasPoint<PositiveDefiniteMatrix>
        interface�CanGetLogProb<PositiveDefiniteMatrix>
        interface�SettableTo<Wishart>
        interface�SettableToProduct<Wishart>
        interface�SettableToProduct<Wishart, Wishart>
        interface�Diffable�
��������interface�SettableToUniform�
��������interface�Sampleable<PositiveDefiniteMatrix>
        interface�SettableToRatio<Wishart>
        interface�SettableToRatio<Wishart, Wishart>
        interface�SettableToPower<Wishart>
        interface�CanGetMean<PositiveDefiniteMatrix>
        interface�CanGetVariance<PositiveDefiniteMatrix>
        interface�CanGetMeanAndVariance<PositiveDefiniteMatrix, PositiveDefiniteMatrix>
        interface�CanSetMeanAndVariance<PositiveDefiniteMatrix, PositiveDefiniteMatrix>
        interface�CanGetLogAverageOf<Wishart>
        interface�CanGetLogAverageOfPower<Wishart>
        interface�SettableToWeightedSum<Wishart>
        interface�CanGetAverageLog<Wishart>
        interface�CanGetLogNormalizer�
����end

[SerializableAttribute]
[Quality(QualityBand::Mature)]
public�ref class�Wishart : IDistribution<PositiveDefiniteMatrix^>, 
	ICloneable, HasPoint<PositiveDefiniteMatrix^>, CanGetLogProb<PositiveDefiniteMatrix^>, 
	SettableTo<Wishart^>, SettableToProduct<Wishart^>, SettableToProduct<Wishart^, Wishart^>, 
	Diffable, SettableToUniform, Sampleable<PositiveDefiniteMatrix^>, SettableToRatio<Wishart^>, 
	SettableToRatio<Wishart^, Wishart^>, SettableToPower<Wishart^>, 
	CanGetMean<PositiveDefiniteMatrix^>, CanGetVariance<PositiveDefiniteMatrix^>, CanGetMeanAndVariance<PositiveDefiniteMatrix^, PositiveDefiniteMatrix^>, 
	CanSetMeanAndVariance<PositiveDefiniteMatrix^, PositiveDefiniteMatrix^>, CanGetLogAverageOf<Wishart^>, 
	CanGetLogAverageOfPower<Wishart^>, SettableToWeightedSum<Wishart^>, CanGetAverageLog<Wishart^>, 
	CanGetLogNormalizer

[SerializableAttribute]
[Quality(QualityBand::Mature)]
public�ref class�Wishart : IDistribution<PositiveDefiniteMatrix^>, 
	ICloneable, HasPoint<PositiveDefiniteMatrix^>, CanGetLogProb<PositiveDefiniteMatrix^>, 
	SettableTo<Wishart^>, SettableToProduct<Wishart^>, SettableToProduct<Wishart^, Wishart^>, 
	Diffable, SettableToUniform, Sampleable<PositiveDefiniteMatrix^>, SettableToRatio<Wishart^>, 
	SettableToRatio<Wishart^, Wishart^>, SettableToPower<Wishart^>, 
	CanGetMean<PositiveDefiniteMatrix^>, CanGetVariance<PositiveDefiniteMatrix^>, CanGetMeanAndVariance<PositiveDefiniteMatrix^, PositiveDefiniteMatrix^>, 
	CanSetMeanAndVariance<PositiveDefiniteMatrix^, PositiveDefiniteMatrix^>, CanGetLogAverageOf<Wishart^>, 
	CanGetLogAverageOfPower<Wishart^>, SettableToWeightedSum<Wishart^>, CanGetAverageLog<Wishart^>, 
	CanGetLogNormalizer

<SerializableAttribute> _
<Quality(QualityBand.Mature)> _
Public�Class�Wishart _
	Implements�IDistribution(Of�PositiveDefiniteMatrix), ICloneable,  _
	HasPoint(Of�PositiveDefiniteMatrix), CanGetLogProb(Of�PositiveDefiniteMatrix), SettableTo(Of�Wishart),  _
	SettableToProduct(Of�Wishart), SettableToProduct(Of�Wishart, Wishart),  _
	Diffable, SettableToUniform, Sampleable(Of�PositiveDefiniteMatrix), SettableToRatio(Of�Wishart),  _
	SettableToRatio(Of�Wishart, Wishart), SettableToPower(Of�Wishart),  _
	CanGetMean(Of�PositiveDefiniteMatrix), CanGetVariance(Of�PositiveDefiniteMatrix), CanGetMeanAndVariance(Of�PositiveDefiniteMatrix, PositiveDefiniteMatrix),  _
	CanSetMeanAndVariance(Of�PositiveDefiniteMatrix, PositiveDefiniteMatrix), CanGetLogAverageOf(Of�Wishart),  _
	CanGetLogAverageOfPower(Of�Wishart), SettableToWeightedSum(Of�Wishart), CanGetAverageLog(Of�Wishart),  _
	CanGetLogNormalizer

<SerializableAttribute> _
<Quality(QualityBand.Mature)> _
Public�Class�Wishart _
	Implements�IDistribution(Of�PositiveDefiniteMatrix), ICloneable,  _
	HasPoint(Of�PositiveDefiniteMatrix), CanGetLogProb(Of�PositiveDefiniteMatrix), SettableTo(Of�Wishart),  _
	SettableToProduct(Of�Wishart), SettableToProduct(Of�Wishart, Wishart),  _
	Diffable, SettableToUniform, Sampleable(Of�PositiveDefiniteMatrix), SettableToRatio(Of�Wishart),  _
	SettableToRatio(Of�Wishart, Wishart), SettableToPower(Of�Wishart),  _
	CanGetMean(Of�PositiveDefiniteMatrix), CanGetVariance(Of�PositiveDefiniteMatrix), CanGetMeanAndVariance(Of�PositiveDefiniteMatrix, PositiveDefiniteMatrix),  _
	CanSetMeanAndVariance(Of�PositiveDefiniteMatrix, PositiveDefiniteMatrix), CanGetLogAverageOf(Of�Wishart),  _
	CanGetLogAverageOfPower(Of�Wishart), SettableToWeightedSum(Of�Wishart), CanGetAverageLog(Of�Wishart),  _
	CanGetLogNormalizer

Remarks

In the matrix case, the distribution is p(X) = |X|^(a-(d+1)/2)*exp(-tr(X*B))*|B|^a/Gamma_d(a). In this code, the a parameter is called the "Shape" and the B parameter is called the "Rate". The mean of the distribution is a/B and the diagonal variance is var(X_ii) = a*C_ii^2 where C=inv(B). The non-diagonal variances are var(X_ij) = a*0.5*(C_ij^2 + C_ii*C_jj) where C=inv(B).

The distribution is represented by a one-dimensional Vector for a and a PositiveDefiniteMatrix for B. Because both are Cursors, any Wishart instance can be used as a cursor.