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)
monoandroid
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 bool IsUniform();
}
}
.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 monoandroid | |
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 framework does not have platform annotations. |
- Built-in API
- Package-provided API