VectorGaussian
VectorGaussian()
VectorGaussian(Int32)
VectorGaussian(VectorGaussian)
VectorGaussian(Double, Double)
VectorGaussian(Vector, PositiveDefiniteMatrix)
Dimension
IsPointMass
MeanTimesPrecision
Point
Precision
Clone()
Copy(VectorGaussian)
Equals(Object)
FromCursors(Vector, PositiveDefiniteMatrix)
FromDerivatives(Vector, Vector, PositiveDefiniteMatrix, Boolean)
FromMeanAndPrecision(Double, Double)
FromMeanAndPrecision(Vector, PositiveDefiniteMatrix)
FromMeanAndVariance(Double, Double)
FromMeanAndVariance(Vector, PositiveDefiniteMatrix)
FromNatural(Vector, PositiveDefiniteMatrix)
GetAverageLog(VectorGaussian)
GetHashCode()
GetLogAverageOf(VectorGaussian)
GetLogAverageOfPower(VectorGaussian, Double)
GetLogNormalizer()
GetLogProb(Vector)
GetLogProb(Vector, LowerTriangularMatrix, Vector)
GetLogProb(Vector, Vector, PositiveDefiniteMatrix)
GetLogProb(Vector, Vector, PositiveDefiniteMatrix, LowerTriangularMatrix, Vector)
GetLogProbPrep()
GetMarginal(Int32)
GetMarginal(Int32, VectorGaussian)
GetMean()
GetMean(Vector)
GetMean(Vector, PositiveDefiniteMatrix)
GetMeanAndPrecision(Vector, PositiveDefiniteMatrix)
GetMeanAndVariance(Vector, PositiveDefiniteMatrix)
GetMode()
GetVariance()
GetVariance(PositiveDefiniteMatrix)
IsProper()
IsUniform()
MaxDiff(Object)
PointMass(Double)
PointMass(Vector)
Sample()
Sample(Vector)
Sample(Vector, LowerTriangularMatrix)
Sample(Vector, PositiveDefiniteMatrix)
SampleFromMeanAndVariance(Vector, PositiveDefiniteMatrix)
SamplePrep()
SetMeanAndPrecision(Vector, PositiveDefiniteMatrix)
SetMeanAndVariance(Vector, PositiveDefiniteMatrix)
SetNatural(Vector, PositiveDefiniteMatrix)
SetTo(VectorGaussian)
SetToPointMass()
SetToPower(VectorGaussian, Double)
SetToProduct(VectorGaussian, VectorGaussian)
SetToRatio(VectorGaussian, VectorGaussian, Boolean)
SetToSum(Double, VectorGaussian, Double, VectorGaussian)
SetToUniform()
ToString()
Uniform(Int32)
WeightedSum<T>(T, Int32, Double, T, Double, T)
operator *(VectorGaussian, VectorGaussian)
operator /(VectorGaussian, VectorGaussian)
operator ^(VectorGaussian, Double)
net10.0-windows7.0
namespace Microsoft.ML.Probabilistic.Distributions
{
[DataContract]
[Quality(QualityBand.Mature)]
public class VectorGaussian : CanGetAverageLog<VectorGaussian>, CanGetLogAverageOf<VectorGaussian>, CanGetLogAverageOfPower<VectorGaussian>, CanGetLogNormalizer, CanGetLogProb<Vector>, CanGetLogProbPrep<VectorGaussian, Vector>, CanGetMean<DenseVector>, CanGetMeanAndVariance<Vector, PositiveDefiniteMatrix>, CanGetMode<DenseVector>, CanGetVariance<PositiveDefiniteMatrix>, CanSamplePrep<VectorGaussian, Vector>, CanSetMeanAndVariance<Vector, PositiveDefiniteMatrix>, HasPoint<Vector>, IDistribution, IDistribution<Vector>, Sampleable<Vector>, SettableToUniform, Diffable, SettableTo<VectorGaussian>, SettableToPower<VectorGaussian>, SettableToProduct<VectorGaussian>, SettableToProduct<VectorGaussian, VectorGaussian>, SettableToRatio<VectorGaussian>, SettableToRatio<VectorGaussian, VectorGaussian>, SettableToWeightedSum<VectorGaussian>, ICloneable
{
public void SetToSum(double weight1, VectorGaussian dist1, double weight2, VectorGaussian dist2);
}
}
.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 net10.0 | |
Platforms | This API is only available when you target a specific platform: |
Windows | 7.0 |
Information specific to net10.0-windows7.0 | |
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