Class BooleanAreEqualOp

Provides outgoing messages for AreEqual(Boolean, Boolean), given random arguments to the function.

Inheritance

Object

BooleanAreEqualOp

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), "AreEqual", new Type[]{typeof(bool), typeof(bool)})]
[Quality(QualityBand.Mature)]
public static class BooleanAreEqualOp

Remarks

This factor is symmetric among all three arguments.

Methods

AAverageConditional(Bernoulli, Bernoulli)

EP message to a.

Declaration

public static Bernoulli AAverageConditional(Bernoulli areEqual, Bernoulli B)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`. Must be a proper distribution. If uniform, the result will be uniform.
Bernoulli	B	Incoming message from `b`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	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_(areEqual,b) p(areEqual,b) factor(areEqual,a,b)]/p(a).

Exceptions

Type	Condition
ImproperMessageException	`areEqual` is not a proper distribution.
ImproperMessageException	`B` is not a proper distribution.

AAverageConditional(Bernoulli, Boolean)

EP message to a.

Declaration

public static Bernoulli AAverageConditional(Bernoulli areEqual, bool B)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`. Must be a proper distribution. If uniform, the result will be uniform.
Boolean	B	Constant value for `b`.

Returns

Type	Description
Bernoulli	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_(areEqual) p(areEqual) factor(areEqual,a,b)]/p(a).

Exceptions

Type	Condition
ImproperMessageException	`areEqual` is not a proper distribution.

AAverageConditional(Boolean, Bernoulli)

EP message to a.

Declaration

public static Bernoulli AAverageConditional(bool areEqual, Bernoulli B)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Bernoulli	B	Incoming message from `b`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	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(areEqual,a,b)]/p(a).

Exceptions

Type	Condition
ImproperMessageException	`B` is not a proper distribution.

AAverageConditional(Boolean, Boolean)

EP message to a.

Declaration

public static Bernoulli AAverageConditional(bool areEqual, bool B)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	B	Constant value for `b`.

Returns

Type	Description
Bernoulli	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.

AAverageLogarithm(Bernoulli, Bernoulli)

VMP message to a.

Declaration

public static Bernoulli AAverageLogarithm(Bernoulli areEqual, Bernoulli B)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`. Must be a proper distribution. If uniform, the result will be uniform.
Bernoulli	B	Incoming message from `b`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `a` argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except a. Because the factor is deterministic, areEqual is integrated out before taking the logarithm. The formula is exp(sum_(b) p(b) log(sum_areEqual p(areEqual) factor(areEqual,a,b))).

Exceptions

Type	Condition
ImproperMessageException	`areEqual` is not a proper distribution.
ImproperMessageException	`B` is not a proper distribution.

AAverageLogarithm(Bernoulli, Boolean)

VMP message to a.

Declaration

public static Bernoulli AAverageLogarithm(Bernoulli areEqual, bool B)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`. Must be a proper distribution. If uniform, the result will be uniform.
Boolean	B	Constant value for `b`.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `a` argument.

Remarks

The outgoing message is the factor viewed as a function of a with areEqual integrated out. The formula is sum_areEqual p(areEqual) factor(areEqual,a,b).

Exceptions

Type	Condition
ImproperMessageException	`areEqual` is not a proper distribution.

AAverageLogarithm(Boolean, Bernoulli)

VMP message to a.

Declaration

[NotSupported("Variational Message Passing does not support an AreEqual factor with fixed output.")]
public static Bernoulli AAverageLogarithm(bool areEqual, Bernoulli B)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Bernoulli	B	Incoming message from `b`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `a` argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except a. The formula is exp(sum_(b) p(b) log(factor(areEqual,a,b))).

Exceptions

Type	Condition
ImproperMessageException	`B` is not a proper distribution.

AAverageLogarithm(Boolean, Boolean)

VMP message to a.

Declaration

public static Bernoulli AAverageLogarithm(bool areEqual, bool B)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	B	Constant value for `b`.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `a` argument.

Remarks

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

AreEqualAverageConditional(Bernoulli, Bernoulli)

EP message to areEqual.

Declaration

public static Bernoulli AreEqualAverageConditional(Bernoulli A, Bernoulli B)

Parameters

Type	Name	Description
Bernoulli	A	Incoming message from `a`. Must be a proper distribution. If uniform, the result will be uniform.
Bernoulli	B	Incoming message from `b`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	The outgoing EP message to the `areEqual` argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	`A` is not a proper distribution.
ImproperMessageException	`B` is not a proper distribution.

AreEqualAverageConditional(Bernoulli, Boolean)

EP message to areEqual.

Declaration

public static Bernoulli AreEqualAverageConditional(Bernoulli A, bool B)

Parameters

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

Returns

Type	Description
Bernoulli	The outgoing EP message to the `areEqual` argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	`A` is not a proper distribution.

AreEqualAverageConditional(Boolean, Bernoulli)

EP message to areEqual.

Declaration

public static Bernoulli AreEqualAverageConditional(bool A, Bernoulli B)

Parameters

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

Returns

Type	Description
Bernoulli	The outgoing EP message to the `areEqual` argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	`B` is not a proper distribution.

AreEqualAverageConditional(Boolean, Boolean)

EP message to areEqual.

Declaration

public static Bernoulli AreEqualAverageConditional(bool A, bool B)

Parameters

Type	Name	Description
Boolean	A	Constant value for `a`.
Boolean	B	Constant value for `b`.

Returns

Type	Description
Bernoulli	The outgoing EP message to the `areEqual` argument.

Remarks

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

AreEqualAverageLogarithm(Bernoulli, Bernoulli)

VMP message to areEqual.

Declaration

public static Bernoulli AreEqualAverageLogarithm(Bernoulli A, Bernoulli B)

Parameters

Type	Name	Description
Bernoulli	A	Incoming message from `a`. Must be a proper distribution. If uniform, the result will be uniform.
Bernoulli	B	Incoming message from `b`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `areEqual` argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	`A` is not a proper distribution.
ImproperMessageException	`B` is not a proper distribution.

AreEqualAverageLogarithm(Bernoulli, Boolean)

VMP message to areEqual.

Declaration

public static Bernoulli AreEqualAverageLogarithm(Bernoulli A, bool B)

Parameters

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

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `areEqual` argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	`A` is not a proper distribution.

AreEqualAverageLogarithm(Boolean, Bernoulli)

VMP message to areEqual.

Declaration

public static Bernoulli AreEqualAverageLogarithm(bool A, Bernoulli B)

Parameters

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

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `areEqual` argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	`B` is not a proper distribution.

AreEqualAverageLogarithm(Boolean, Boolean)

VMP message to areEqual.

Declaration

public static Bernoulli AreEqualAverageLogarithm(bool A, bool B)

Parameters

Type	Name	Description
Boolean	A	Constant value for `a`.
Boolean	B	Constant value for `b`.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `areEqual` argument.

Remarks

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

AverageLogFactor()

Evidence message for VMP.

Declaration

public static double AverageLogFactor()

Returns

Type	Description
Double	Zero.

Remarks

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

AverageLogFactor(Boolean, Boolean, Boolean)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(bool areEqual, bool a, bool b)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	a	Constant value for `a`.
Boolean	b	Constant value for `b`.

Returns

Type	Description
Double	Zero.

Remarks

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

BAverageConditional(Bernoulli, Bernoulli)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(Bernoulli areEqual, Bernoulli A)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`. Must be a proper distribution. If uniform, the result will be uniform.
Bernoulli	A	Incoming message from `a`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	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_(areEqual,a) p(areEqual,a) factor(areEqual,a,b)]/p(b).

Exceptions

Type	Condition
ImproperMessageException	`areEqual` is not a proper distribution.
ImproperMessageException	`A` is not a proper distribution.

BAverageConditional(Bernoulli, Boolean)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(Bernoulli areEqual, bool A)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`. Must be a proper distribution. If uniform, the result will be uniform.
Boolean	A	Constant value for `a`.

Returns

Type	Description
Bernoulli	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_(areEqual) p(areEqual) factor(areEqual,a,b)]/p(b).

Exceptions

Type	Condition
ImproperMessageException	`areEqual` is not a proper distribution.

BAverageConditional(Boolean, Bernoulli)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(bool areEqual, Bernoulli A)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Bernoulli	A	Incoming message from `a`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	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(areEqual,a,b)]/p(b).

Exceptions

Type	Condition
ImproperMessageException	`A` is not a proper distribution.

BAverageConditional(Boolean, Boolean)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(bool areEqual, bool A)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	A	Constant value for `a`.

Returns

Type	Description
Bernoulli	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.

BAverageLogarithm(Bernoulli, Bernoulli)

VMP message to b.

Declaration

public static Bernoulli BAverageLogarithm(Bernoulli areEqual, Bernoulli A)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`. Must be a proper distribution. If uniform, the result will be uniform.
Bernoulli	A	Incoming message from `a`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `b` argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except b. Because the factor is deterministic, areEqual is integrated out before taking the logarithm. The formula is exp(sum_(a) p(a) log(sum_areEqual p(areEqual) factor(areEqual,a,b))).

Exceptions

Type	Condition
ImproperMessageException	`areEqual` is not a proper distribution.
ImproperMessageException	`A` is not a proper distribution.

BAverageLogarithm(Bernoulli, Boolean)

VMP message to b.

Declaration

public static Bernoulli BAverageLogarithm(Bernoulli areEqual, bool A)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`. Must be a proper distribution. If uniform, the result will be uniform.
Boolean	A	Constant value for `a`.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `b` argument.

Remarks

The outgoing message is the factor viewed as a function of b with areEqual integrated out. The formula is sum_areEqual p(areEqual) factor(areEqual,a,b).

Exceptions

Type	Condition
ImproperMessageException	`areEqual` is not a proper distribution.

BAverageLogarithm(Boolean, Bernoulli)

VMP message to b.

Declaration

[NotSupported("Variational Message Passing does not support an AreEqual factor with fixed output.")]
public static Bernoulli BAverageLogarithm(bool areEqual, Bernoulli A)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Bernoulli	A	Incoming message from `a`. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `b` argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except b. The formula is exp(sum_(a) p(a) log(factor(areEqual,a,b))).

Exceptions

Type	Condition
ImproperMessageException	`A` is not a proper distribution.

BAverageLogarithm(Boolean, Boolean)

VMP message to b.

Declaration

public static Bernoulli BAverageLogarithm(bool areEqual, bool A)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	A	Constant value for `a`.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the `b` argument.

Remarks

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

LogAverageFactor(Bernoulli, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli areEqual, Bernoulli to_areEqual)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`.
Bernoulli	to_areEqual	Outgoing message to `areEqual`.

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

LogAverageFactor(Bernoulli, Boolean, Boolean)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli areEqual, bool a, bool b)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`.
Boolean	a	Constant value for `a`.
Boolean	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_(areEqual) p(areEqual) factor(areEqual,a,b)).

LogAverageFactor(Boolean, Bernoulli, Bernoulli, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool areEqual, Bernoulli A, Bernoulli B, Bernoulli to_A)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Bernoulli	A	Incoming message from `a`.
Bernoulli	B	Incoming message from `b`.
Bernoulli	to_A	Outgoing message to `A`.

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(areEqual,a,b)).

LogAverageFactor(Boolean, Bernoulli, Boolean, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool areEqual, Bernoulli A, bool B, Bernoulli to_A)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Bernoulli	A	Incoming message from `a`.
Boolean	B	Constant value for `b`.
Bernoulli	to_A	Outgoing message to `A`.

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(areEqual,a,b)).

LogAverageFactor(Boolean, Boolean, Bernoulli, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool areEqual, bool A, Bernoulli B, Bernoulli to_B)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	A	Constant value for `a`.
Bernoulli	B	Incoming message from `b`.
Bernoulli	to_B	Outgoing message to `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(areEqual,a,b)).

LogAverageFactor(Boolean, Boolean, Boolean)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool areEqual, bool a, bool b)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	a	Constant value for `a`.
Boolean	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(areEqual,a,b)).

LogEvidenceRatio(Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(Bernoulli areEqual)

Parameters

Type	Name	Description
Bernoulli	areEqual	Incoming message from `areEqual`.

Returns

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

Remarks

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

LogEvidenceRatio(Boolean, Bernoulli, Bernoulli, Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool areEqual, Bernoulli A, Bernoulli B, Bernoulli to_A)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Bernoulli	A	Incoming message from `a`.
Bernoulli	B	Incoming message from `b`.
Bernoulli	to_A	Outgoing message to `A`.

Returns

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

Remarks

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

LogEvidenceRatio(Boolean, Bernoulli, Boolean, Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool areEqual, Bernoulli A, bool B, Bernoulli to_A)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Bernoulli	A	Incoming message from `a`.
Boolean	B	Constant value for `b`.
Bernoulli	to_A	Outgoing message to `A`.

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(areEqual,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Boolean, Bernoulli, Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool areEqual, bool A, Bernoulli B, Bernoulli to_B)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	A	Constant value for `a`.
Bernoulli	B	Incoming message from `b`.
Bernoulli	to_B	Outgoing message to `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(areEqual,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Boolean, Boolean)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool areEqual, bool a, bool b)

Parameters

Type	Name	Description
Boolean	areEqual	Constant value for `areEqual`.
Boolean	a	Constant value for `a`.
Boolean	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(factor(areEqual,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.