VectorGaussianMoments
VectorGaussianMoments()
VectorGaussianMoments(Int32)
VectorGaussianMoments(VectorGaussianMoments)
VectorGaussianMoments(Double, Double)
VectorGaussianMoments(Vector, PositiveDefiniteMatrix)
Dimension
IsPointMass
Mean
Point
Variance
Clone()
Copy(VectorGaussianMoments)
Equals(Object)
FromMeanAndPrecision(Double, Double)
FromMeanAndPrecision(Vector, PositiveDefiniteMatrix)
FromMeanAndVariance(Double, Double)
FromMeanAndVariance(Vector, PositiveDefiniteMatrix)
GetAverageLog(VectorGaussianMoments)
GetHashCode()
GetLogAverageOf(VectorGaussianMoments)
GetLogAverageOfPower(VectorGaussianMoments, Double)
GetLogNormalizer()
GetLogProb(Vector)
GetMarginal(Int32)
GetMarginal(Int32, VectorGaussianMoments)
GetMean()
GetMean(Vector)
GetMeanAndPrecision(Vector, PositiveDefiniteMatrix)
GetMeanAndVariance(Vector, PositiveDefiniteMatrix)
GetMode()
GetVariance()
GetVariance(PositiveDefiniteMatrix)
IsProper()
IsUniform()
MaxDiff(Object)
PointMass(Double)
PointMass(Vector)
Sample()
Sample(Vector)
SetMeanAndPrecision(Vector, PositiveDefiniteMatrix)
SetMeanAndVariance(Vector, PositiveDefiniteMatrix)
SetNatural(Vector, PositiveDefiniteMatrix)
SetTo(VectorGaussianMoments)
SetToPointMass()
SetToPower(VectorGaussianMoments, Double)
SetToProduct(VectorGaussianMoments, VectorGaussianMoments)
SetToProduct(VectorGaussianMoments, IList<Gaussian>)
SetToRatio(VectorGaussianMoments, VectorGaussianMoments, Boolean)
SetToSum(Double, VectorGaussianMoments, Double, VectorGaussianMoments)
SetToUniform()
ToString()
Uniform(Int32)
WeightedSum<T>(T, Int32, Double, T, Double, T)
operator *(VectorGaussianMoments, VectorGaussianMoments)
operator /(VectorGaussianMoments, VectorGaussianMoments)
operator ^(VectorGaussianMoments, Double)
net5.0
namespace Microsoft.ML.Probabilistic.Distributions
{
[DataContract]
[Quality(QualityBand.Mature)]
public class VectorGaussianMoments : CanGetAverageLog<VectorGaussianMoments>, CanGetLogAverageOf<VectorGaussianMoments>, CanGetLogAverageOfPower<VectorGaussianMoments>, CanGetLogNormalizer, CanGetLogProb<Vector>, CanGetMean<DenseVector>, CanGetMeanAndVariance<Vector, PositiveDefiniteMatrix>, CanGetMode<DenseVector>, CanGetVariance<PositiveDefiniteMatrix>, CanSetMeanAndVariance<Vector, PositiveDefiniteMatrix>, HasPoint<Vector>, IDistribution, IDistribution<Vector>, Sampleable<Vector>, SettableToUniform, Diffable, SettableTo<VectorGaussianMoments>, SettableToPower<VectorGaussianMoments>, SettableToProduct<VectorGaussianMoments>, SettableToProduct<VectorGaussianMoments, VectorGaussianMoments>, SettableToRatio<VectorGaussianMoments>, SettableToRatio<VectorGaussianMoments, VectorGaussianMoments>, SettableToWeightedSum<VectorGaussianMoments>, ICloneable
{
public void SetToProduct(VectorGaussianMoments g1, VectorGaussianMoments g2);
}
}
.NET | 5.06.07.08.09.010.0 |
---|---|
.NET Core | 2.02.12.23.03.1 |
.NET Framework | 4.6.14.6.24.74.7.14.7.24.84.8.1 |
.NET Standard | 2.02.1 |
Information specific to net5.0 | |
Assembly | Microsoft.ML.Probabilistic , Version=0.4.2403.801, PublicKeyToken=e4813102a62778da |
Referencing | Your project needs a package reference to |
Package | Microsoft.ML.Probabilistic (0.4.2403.801) netstandard2.0 |
Platform Restrictions | This API is supported on all platforms. |
- Built-in API
- Package-provided API