- 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 PositiveDefiniteMatrix Precision { get; set; }
    }
}
            | .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 | The property getter is supported on all platforms. The property setter is supported on all platforms. | 
- Built-in API
- Package-provided API