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    Class GaussianOp_PointPrecision

    This class defines specializations for the case where precision is a point mass. These methods have fewer inputs, allowing more efficient schedules.

    Inheritance
    Object
    GaussianOpBase
    GaussianOp_PointPrecision
    Inherited Members
    GaussianOpBase.SampleAverageConditional(Double, Double)
    GaussianOpBase.MeanAverageConditional(Double, Double)
    GaussianOpBase.PrecisionAverageConditional(Double, Double)
    GaussianOpBase.SampleAverageConditional(Gaussian, Double)
    GaussianOpBase.MeanAverageConditional(Gaussian, Double)
    GaussianOpBase.LogAverageFactor(Double, Double, Double)
    GaussianOpBase.LogAverageFactor(Gaussian, Gaussian, Double)
    GaussianOpBase.LogAverageFactor(Gaussian, Double, Double)
    GaussianOpBase.LogAverageFactor(Double, Gaussian, Double)
    GaussianOpBase.LogAverageFactor(Double, Double, Gamma)
    GaussianOpBase.TPdfLn(Double, Double, Double)
    GaussianOpBase.LogEvidenceRatio(Double, Double, Double)
    GaussianOpBase.LogEvidenceRatio(Gaussian, Gaussian, Double)
    GaussianOpBase.LogEvidenceRatio(Gaussian, Double, Double)
    GaussianOpBase.LogEvidenceRatio(Double, Gaussian, Double)
    GaussianOpBase.LogEvidenceRatio(Double, Double, Gamma)
    Object.Equals(Object)
    Object.Equals(Object, Object)
    Object.GetHashCode()
    Object.GetType()
    Object.MemberwiseClone()
    Object.ReferenceEquals(Object, Object)
    Object.ToString()
    Namespace: Microsoft.ML.Probabilistic.Factors
    Assembly: Microsoft.ML.Probabilistic.dll
    Syntax
    [FactorMethod(typeof(Gaussian), "Sample", new Type[]{typeof(double), typeof(double)}, Default = false)]
    [FactorMethod(new string[]{"sample", "mean", "precision"}, typeof(Factor), "Gaussian", new Type[]{}, Default = false)]
    [Quality(QualityBand.Preview)]
    public class GaussianOp_PointPrecision : GaussianOpBase

    Methods

    LogEvidenceRatio(Gaussian, Gaussian, Gamma)

    Declaration
    public static double LogEvidenceRatio(Gaussian sample, Gaussian mean, Gamma precision)
    Parameters
    Type Name Description
    Gaussian sample
    Gaussian mean
    Gamma precision
    Returns
    Type Description
    Double

    LogEvidenceRatio(Double, Gaussian, Gamma)

    Declaration
    public static double LogEvidenceRatio(double sample, Gaussian mean, Gamma precision)
    Parameters
    Type Name Description
    Double sample
    Gaussian mean
    Gamma precision
    Returns
    Type Description
    Double

    MeanAverageConditional(Gaussian, Gamma)

    Declaration
    public static Gaussian MeanAverageConditional(Gaussian sample, Gamma precision)
    Parameters
    Type Name Description
    Gaussian sample
    Gamma precision
    Returns
    Type Description
    Gaussian

    PrecisionAverageConditional(Gaussian, Gaussian, Gamma)

    Declaration
    public static Gamma PrecisionAverageConditional(Gaussian sample, Gaussian mean, Gamma precision)
    Parameters
    Type Name Description
    Gaussian sample
    Gaussian mean
    Gamma precision
    Returns
    Type Description
    Gamma

    SampleAverageConditional(Gaussian, Gamma)

    Declaration
    public static Gaussian SampleAverageConditional(Gaussian mean, Gamma precision)
    Parameters
    Type Name Description
    Gaussian mean
    Gamma precision
    Returns
    Type Description
    Gaussian
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