VectorGaussian Class

Infer.NET Documentation

Microsoft Research, Cambridge

Represents a multivariate Gaussian distribution.

Inheritance Hierarchy

System�Object
��MicrosoftResearch.Infer.Distributions�VectorGaussian

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

Syntax

C++

Copy to Clipboard Print

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

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

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

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

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

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

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

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

Remarks

The distribution is parameterized by MeanTimesPrecision and Precision. Precision is the inverse of the variance, so a Gaussian with mean m and variance v is represented as Precision = inv(v), MeanTimesPrecision = inv(v)*m.

Some special cases: If the precision is zero, then the distribution is uniform. If the precision is infinite along the diagonal, then the distribution is a point mass. The Point property gives the location of the point mass. If precision[i,i] is infinite, then the distribution is a point mass along dimension i. Point[i] gives the mean. The rest of the row and column of precision must be zero.

The formula for the distribution is: N(x;m,v) = |2*pi*v|^(-d/2) * exp(-0.5 (x-m)' inv(v) (x-m)). When v=0, this reduces to delta(x-m). When v=infinity, the density is redefined to be 1. When v is singular, the density is redefined to be exp(-0.5 x' inv(v) x + x' inv(v) m), i.e. we drop the terms |2*pi*v|^(-d/2) * exp(-0.5 m' inv(v) m).