Class GammaRatioOp

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

Inheritance

Object

GammaRatioOp

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(typeof(Factor), "Ratio", new Type[]{typeof(double), typeof(double)})]
[Quality(QualityBand.Preview)]
public static class GammaRatioOp

Methods

AAverageConditional(Gamma, Double)

EP message to a.

Declaration

public static Gamma AAverageConditional(Gamma ratio, double B)

Parameters

Type	Name	Description
Gamma	ratio	Incoming message from ratio. Must be a proper distribution. If uniform, the result will be uniform.
Double	B	Constant value for b.

Returns

Type	Description
Gamma	The outgoing EP message to the a argument.

Remarks

The outgoing message is a distribution matching the moments of a as the random arguments are varied. The formula is proj[p(a) sum_(ratio) p(ratio) factor(ratio,a,b)]/p(a).

Exceptions

Type	Condition
ImproperMessageException	ratio is not a proper distribution.

AAverageConditional(Double, Gamma)

EP message to a.

Declaration

public static Gamma AAverageConditional(double ratio, Gamma B)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Gamma	B	Incoming message from b.

Returns

Type	Description
Gamma	The outgoing EP message to the a argument.

Remarks

The outgoing message is a distribution matching the moments of a as the random arguments are varied. The formula is proj[p(a) sum_(b) p(b) factor(ratio,a,b)]/p(a).

AAverageConditional(Double, Double)

EP message to a.

Declaration

public static Gamma AAverageConditional(double ratio, double B)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Double	B	Constant value for b.

Returns

Type	Description
Gamma	The outgoing EP message to the a argument.

Remarks

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

BAverageConditional(Gamma, Double)

EP message to b.

Declaration

public static GammaPower BAverageConditional(Gamma ratio, double A)

Parameters

Type	Name	Description
Gamma	ratio	Incoming message from ratio. Must be a proper distribution. If uniform, the result will be uniform.
Double	A	Constant value for a.

Returns

Type	Description
GammaPower	The outgoing EP message to the b argument.

Remarks

The outgoing message is a distribution matching the moments of b as the random arguments are varied. The formula is proj[p(b) sum_(ratio) p(ratio) factor(ratio,a,b)]/p(b).

Exceptions

Type	Condition
ImproperMessageException	ratio is not a proper distribution.

BAverageConditional(Double, Gamma)

EP message to b.

Declaration

public static Gamma BAverageConditional(double ratio, Gamma A)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Gamma	A	Incoming message from a.

Returns

Type	Description
Gamma	The outgoing EP message to the b argument.

Remarks

The outgoing message is a distribution matching the moments of b as the random arguments are varied. The formula is proj[p(b) sum_(a) p(a) factor(ratio,a,b)]/p(b).

BAverageConditional(Double, Double)

EP message to b.

Declaration

public static Gamma BAverageConditional(double ratio, double A)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Double	A	Constant value for a.

Returns

Type	Description
Gamma	The outgoing EP message to the b argument.

Remarks

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

LogAverageFactor(Gamma, Gamma, Double)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Gamma ratio, Gamma a, double b)

Parameters

Type	Name	Description
Gamma	ratio	Incoming message from ratio.
Gamma	a	Incoming message from a.
Double	b	Constant value for b.

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_(ratio,a) p(ratio,a) factor(ratio,a,b)).

LogAverageFactor(Double, Gamma, Gamma)

Evidence message for EP.

Declaration

public static double LogAverageFactor(double ratio, Gamma A, Gamma B)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Gamma	A	Incoming message from a.
Gamma	B	Incoming message from b.

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_(a,b) p(a,b) factor(ratio,a,b)).

LogAverageFactor(Double, Gamma, Double)

Evidence message for EP.

Declaration

public static double LogAverageFactor(double ratio, Gamma a, double b)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Gamma	a	Incoming message from a.
Double	b	Constant value for b.

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_(a) p(a) factor(ratio,a,b)).

LogAverageFactor(Double, Double, Gamma)

Evidence message for EP.

Declaration

public static double LogAverageFactor(double ratio, double A, Gamma B)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Double	A	Constant value for a.
Gamma	B	Incoming message from b.

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_(b) p(b) factor(ratio,a,b)).

LogAverageFactor(Double, Double, Double)

Evidence message for EP.

Declaration

public static double LogAverageFactor(double ratio, double A, double B)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Double	A	Constant value for a.
Double	B	Constant value for b.

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(ratio,a,b)).

LogEvidenceRatio(Gamma, Gamma, Double)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(Gamma ratio, Gamma a, double b)

Parameters

Type	Name	Description
Gamma	ratio	Incoming message from ratio.
Gamma	a	Incoming message from a.
Double	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(ratio,a) p(ratio,a) factor(ratio,a,b) / sum_ratio p(ratio) messageTo(ratio)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Double, Gamma, Double)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(double ratio, Gamma a, double b)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Gamma	a	Incoming message from a.
Double	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(a) p(a) factor(ratio,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Double, Double, Gamma)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(double ratio, double a, Gamma b)

Parameters

Type	Name	Description
Double	ratio	Constant value for ratio.
Double	a	Constant value for a.
Gamma	b	Incoming message from b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(b) p(b) factor(ratio,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

RatioAverageConditional(Gamma, Double)

EP message to ratio.

Declaration

public static Gamma RatioAverageConditional(Gamma A, double B)

Parameters

Type	Name	Description
Gamma	A	Incoming message from a. Must be a proper distribution. If uniform, the result will be uniform.
Double	B	Constant value for b.

Returns

Type	Description
Gamma	The outgoing EP message to the ratio argument.

Remarks

The outgoing message is a distribution matching the moments of ratio as the random arguments are varied. The formula is proj[p(ratio) sum_(a) p(a) factor(ratio,a,b)]/p(ratio).

Exceptions

Type	Condition
ImproperMessageException	A is not a proper distribution.

RatioAverageConditional(Double, Gamma)

EP message to ratio.

Declaration

public static GammaPower RatioAverageConditional(double A, Gamma B)

Parameters

Type	Name	Description
Double	A	Constant value for a.
Gamma	B	Incoming message from b.

Returns

Type	Description
GammaPower	The outgoing EP message to the ratio argument.

Remarks

The outgoing message is a distribution matching the moments of ratio as the random arguments are varied. The formula is proj[p(ratio) sum_(b) p(b) factor(ratio,a,b)]/p(ratio).