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)
net6.0-windows
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 double GetLogProb(Vector x);
}
}
.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 net6.0 | |
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