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    Class GammaFromMeanAndVarianceOp

    Provides outgoing messages for SampleFromMeanAndVariance(Double, Double), given random arguments to the function.

    Inheritance
    Object
    GammaFromMeanAndVarianceOp
    Inherited Members
    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(new string[]{"sample", "mean", "variance"}, typeof(Gamma), "SampleFromMeanAndVariance", new Type[]{})]
    [Quality(QualityBand.Stable)]
    public static class GammaFromMeanAndVarianceOp

    Methods

    AverageLogFactor(Double, Double, Double)

    Evidence message for VMP.

    Declaration
    public static double AverageLogFactor(double sample, double mean, double variance)
    Parameters
    Type Name Description
    Double sample

    Constant value for sample.

    Double mean

    Constant value for mean.

    Double variance

    Constant value for variance.

    Returns
    Type Description
    Double

    Average of the factor's log-value across the given argument distributions.

    Remarks

    The formula for the result is log(factor(sample,mean,variance)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

    LogAverageFactor(Gamma, Gamma)

    Evidence message for EP.

    Declaration
    public static double LogAverageFactor(Gamma sample, Gamma to_sample)
    Parameters
    Type Name Description
    Gamma sample

    Incoming message from sample.

    Gamma to_sample

    Outgoing message to sample.

    Returns
    Type Description
    Double

    Logarithm of the factor's average value across the given argument distributions.

    Remarks

    The formula for the result is log(sum_(sample) p(sample) factor(sample,mean,variance)).

    LogAverageFactor(Double, Double, Double)

    Evidence message for EP.

    Declaration
    public static double LogAverageFactor(double sample, double mean, double variance)
    Parameters
    Type Name Description
    Double sample

    Constant value for sample.

    Double mean

    Constant value for mean.

    Double variance

    Constant value for variance.

    Returns
    Type Description
    Double

    Logarithm of the factor's average value across the given argument distributions.

    Remarks

    The formula for the result is log(factor(sample,mean,variance)).

    LogEvidenceRatio(Double, Double, Double)

    Evidence message for EP.

    Declaration
    public static double LogEvidenceRatio(double sample, double mean, double variance)
    Parameters
    Type Name Description
    Double sample

    Constant value for sample.

    Double mean

    Constant value for mean.

    Double variance

    Constant value for variance.

    Returns
    Type Description
    Double

    Logarithm of the factor's contribution the EP model evidence.

    Remarks

    The formula for the result is log(factor(sample,mean,variance)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

    SampleAverageConditional(Double, Double)

    EP message to sample.

    Declaration
    public static Gamma SampleAverageConditional(double mean, double variance)
    Parameters
    Type Name Description
    Double mean

    Constant value for mean.

    Double variance

    Constant value for variance.

    Returns
    Type Description
    Gamma

    The outgoing EP message to the sample argument.

    Remarks

    The outgoing message is the factor viewed as a function of sample conditioned on the given values.

    SampleAverageLogarithm(Double, Double)

    VMP message to sample.

    Declaration
    public static Gamma SampleAverageLogarithm(double mean, double variance)
    Parameters
    Type Name Description
    Double mean

    Constant value for mean.

    Double variance

    Constant value for variance.

    Returns
    Type Description
    Gamma

    The outgoing VMP message to the sample argument.

    Remarks

    The outgoing message is the factor viewed as a function of sample conditioned on the given values.

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