Class IsGreaterThanOp

Provides outgoing messages for IsGreaterThan(Int32, Int32), given random arguments to the function.

Inheritance

Object

IsGreaterThanOp

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), "IsGreaterThan", new Type[]{typeof(int), typeof(int)})]
[Quality(QualityBand.Preview)]
public static class IsGreaterThanOp

Remarks

A and B need not have the same dimension.

Methods

AAverageConditional(Bernoulli, Discrete, Discrete)

EP message to a.

Declaration

public static Discrete AAverageConditional(Bernoulli isGreaterThan, Discrete b, Discrete result)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Discrete	b	Incoming message from b.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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_(isGreaterThan,b) p(isGreaterThan,b) factor(isGreaterThan,a,b)]/p(a).

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.

AAverageConditional(Bernoulli, Poisson, Int32)

EP message to a.

Declaration

public static Poisson AAverageConditional(Bernoulli isGreaterThan, Poisson a, int b)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Poisson	a	Incoming message from a. Must be a proper distribution. If uniform, the result will be uniform.
Int32	b	Constant value for b.

Returns

Type	Description
Poisson	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_(isGreaterThan) p(isGreaterThan) factor(isGreaterThan,a,b)]/p(a).

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.
ImproperMessageException	a is not a proper distribution.

AAverageConditional(Bernoulli, Int32, Discrete)

EP message to a.

Declaration

public static Discrete AAverageConditional(Bernoulli isGreaterThan, int b, Discrete result)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Int32	b	Constant value for b.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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_(isGreaterThan) p(isGreaterThan) factor(isGreaterThan,a,b)]/p(a).

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.

AAverageConditional(Boolean, Discrete, Discrete)

EP message to a.

Declaration

public static Discrete AAverageConditional(bool isGreaterThan, Discrete b, Discrete result)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	b	Incoming message from b.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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(isGreaterThan,a,b)]/p(a).

AAverageConditional(Boolean, Int32, Discrete)

EP message to a.

Declaration

public static Discrete AAverageConditional(bool isGreaterThan, int b, Discrete result)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	b	Constant value for b.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

Remarks

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

AAverageLogarithm(Bernoulli, Discrete, Discrete)

VMP message to a.

Declaration

public static Discrete AAverageLogarithm(Bernoulli isGreaterThan, Discrete b, Discrete result)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Discrete	b	Incoming message from b.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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, isGreaterThan is integrated out before taking the logarithm. The formula is exp(sum_(b) p(b) log(sum_isGreaterThan p(isGreaterThan) factor(isGreaterThan,a,b))).

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.

AAverageLogarithm(Bernoulli, Int32, Discrete)

VMP message to a.

Declaration

public static Discrete AAverageLogarithm(Bernoulli isGreaterThan, int b, Discrete result)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Int32	b	Constant value for b.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.

AAverageLogarithm(Boolean, Discrete, Discrete)

VMP message to a.

Declaration

[NotSupported("Variational Message Passing does not support an IsGreaterThan factor with fixed output.")]
public static Discrete AAverageLogarithm(bool isGreaterThan, Discrete b, Discrete result)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	b	Incoming message from b.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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(isGreaterThan,a,b))).

AAverageLogarithm(Boolean, Int32, Discrete)

VMP message to a.

Declaration

public static Discrete AAverageLogarithm(bool isGreaterThan, int b, Discrete result)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	b	Constant value for b.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

Remarks

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

AverageLogFactor(Bernoulli, Discrete, Discrete)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(Bernoulli isGreaterThan, Discrete a, Discrete b)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan.
Discrete	a	Incoming message from a.
Discrete	b	Incoming message from b.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Bernoulli, Discrete, Int32)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(Bernoulli isGreaterThan, Discrete a, int b)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan.
Discrete	a	Incoming message from a.
Int32	b	Constant value for b.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Bernoulli, Int32, Discrete)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(Bernoulli isGreaterThan, int a, Discrete b)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan.
Int32	a	Constant value for a.
Discrete	b	Incoming message from b.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Bernoulli, Int32, Int32)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(Bernoulli isGreaterThan, int a, int b)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan.
Int32	a	Constant value for a.
Int32	b	Constant value for b.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Boolean, Discrete, Discrete)

Evidence message for VMP.

Declaration

[NotSupported("Variational Message Passing does not support an IsGreaterThan factor with fixed output.")]
public static double AverageLogFactor(bool isGreaterThan, Discrete a, Discrete b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	a	Incoming message from a.
Discrete	b	Incoming message from b.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Boolean, Discrete, Int32)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(bool isGreaterThan, Discrete a, int b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	a	Incoming message from a.
Int32	b	Constant value for b.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Boolean, Int32, Discrete)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(bool isGreaterThan, int a, Discrete b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	a	Constant value for a.
Discrete	b	Incoming message from b.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Boolean, Int32, Int32)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(bool isGreaterThan, int a, int b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	a	Constant value for a.
Int32	b	Constant value for b.

Returns

Type	Description
Double	Zero.

Remarks

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

BAverageConditional(Bernoulli, Discrete, Discrete)

EP message to b.

Declaration

public static Discrete BAverageConditional(Bernoulli isGreaterThan, Discrete a, Discrete result)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Discrete	a	Incoming message from a.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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_(isGreaterThan,a) p(isGreaterThan,a) factor(isGreaterThan,a,b)]/p(b).

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.

BAverageConditional(Bernoulli, Int32, Discrete)

EP message to b.

Declaration

public static Discrete BAverageConditional(Bernoulli isGreaterThan, int a, Discrete result)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Int32	a	Constant value for a.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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_(isGreaterThan) p(isGreaterThan) factor(isGreaterThan,a,b)]/p(b).

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.

BAverageConditional(Bernoulli, Int32, Poisson)

EP message to a.

Declaration

public static Poisson BAverageConditional(Bernoulli isGreaterThan, int a, Poisson b)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Int32	a	Incoming message from a. Must be a proper distribution. If uniform, the result will be uniform.
Poisson	b	Constant value for b.

Returns

Type	Description
Poisson	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_(isGreaterThan) p(isGreaterThan) factor(isGreaterThan,a,b)]/p(a).

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.
ImproperMessageException	a is not a proper distribution.

BAverageConditional(Boolean, Discrete, Discrete)

EP message to b.

Declaration

public static Discrete BAverageConditional(bool isGreaterThan, Discrete a, Discrete result)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	a	Incoming message from a.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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(isGreaterThan,a,b)]/p(b).

BAverageConditional(Boolean, Int32, Discrete)

EP message to b.

Declaration

public static Discrete BAverageConditional(bool isGreaterThan, int a, Discrete result)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	a	Constant value for a.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

Remarks

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

BAverageLogarithm(Bernoulli, Discrete, Discrete)

VMP message to b.

Declaration

public static Discrete BAverageLogarithm(Bernoulli isGreaterThan, Discrete a, Discrete result)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Discrete	a	Incoming message from a.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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, isGreaterThan is integrated out before taking the logarithm. The formula is exp(sum_(a) p(a) log(sum_isGreaterThan p(isGreaterThan) factor(isGreaterThan,a,b))).

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.

BAverageLogarithm(Bernoulli, Int32, Discrete)

VMP message to b.

Declaration

public static Discrete BAverageLogarithm(Bernoulli isGreaterThan, int a, Discrete result)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan. Must be a proper distribution. If uniform, the result will be uniform.
Int32	a	Constant value for a.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	isGreaterThan is not a proper distribution.

BAverageLogarithm(Boolean, Discrete, Discrete)

VMP message to b.

Declaration

[NotSupported("Variational Message Passing does not support an IsGreaterThan factor with fixed output.")]
public static Discrete BAverageLogarithm(bool isGreaterThan, Discrete a, Discrete result)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	a	Incoming message from a.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

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(isGreaterThan,a,b))).

BAverageLogarithm(Boolean, Int32, Discrete)

VMP message to b.

Declaration

public static Discrete BAverageLogarithm(bool isGreaterThan, int a, Discrete result)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	a	Constant value for a.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	result

Remarks

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

IsGreaterThanAverageConditional(Binomial, Int32)

EP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageConditional(Binomial a, int b)

Parameters

Type	Name	Description
Binomial	a	Incoming message from a. Must be a proper distribution. If uniform, the result will be uniform.
Int32	b	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the isGreaterThan argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	a is not a proper distribution.

IsGreaterThanAverageConditional(Discrete, Discrete)

EP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageConditional(Discrete a, Discrete b)

Parameters

Type	Name	Description
Discrete	a	Incoming message from a.
Discrete	b	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the isGreaterThan argument.

Remarks

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

IsGreaterThanAverageConditional(Discrete, Int32)

EP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageConditional(Discrete a, int b)

Parameters

Type	Name	Description
Discrete	a	Incoming message from a.
Int32	b	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the isGreaterThan argument.

Remarks

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

IsGreaterThanAverageConditional(Poisson, Int32)

EP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageConditional(Poisson a, int b)

Parameters

Type	Name	Description
Poisson	a	Incoming message from a. Must be a proper distribution. If uniform, the result will be uniform.
Int32	b	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the isGreaterThan argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	a is not a proper distribution.

IsGreaterThanAverageConditional(Int32, Binomial)

EP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageConditional(int a, Binomial b)

Parameters

Type	Name	Description
Int32	a	Constant value for a.
Binomial	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 isGreaterThan argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	b is not a proper distribution.

IsGreaterThanAverageConditional(Int32, Discrete)

EP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageConditional(int a, Discrete b)

Parameters

Type	Name	Description
Int32	a	Constant value for a.
Discrete	b	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the isGreaterThan argument.

Remarks

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

IsGreaterThanAverageConditional(Int32, Poisson)

EP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageConditional(int a, Poisson b)

Parameters

Type	Name	Description
Int32	a	Constant value for a.
Poisson	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 isGreaterThan argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	b is not a proper distribution.

IsGreaterThanAverageLogarithm(Discrete, Discrete)

VMP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageLogarithm(Discrete a, Discrete b)

Parameters

Type	Name	Description
Discrete	a	Incoming message from a.
Discrete	b	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the isGreaterThan argument.

Remarks

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

IsGreaterThanAverageLogarithm(Discrete, Int32)

VMP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageLogarithm(Discrete a, int b)

Parameters

Type	Name	Description
Discrete	a	Incoming message from a.
Int32	b	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the isGreaterThan argument.

Remarks

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

IsGreaterThanAverageLogarithm(Int32, Discrete)

VMP message to isGreaterThan.

Declaration

public static Bernoulli IsGreaterThanAverageLogarithm(int a, Discrete b)

Parameters

Type	Name	Description
Int32	a	Constant value for a.
Discrete	b	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the isGreaterThan argument.

Remarks

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

LogAverageFactor(Bernoulli, Discrete, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli isGreaterThan, Discrete a, Bernoulli to_isGreaterThan)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan.
Discrete	a	Incoming message from a.
Bernoulli	to_isGreaterThan	Outgoing message to isGreaterThan.

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

LogAverageFactor(Bernoulli, Int32, Discrete, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli isGreaterThan, int a, Discrete b, Bernoulli to_isGreaterThan)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan.
Int32	a	Constant value for a.
Discrete	b	Incoming message from b.
Bernoulli	to_isGreaterThan	Outgoing message to isGreaterThan.

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

LogAverageFactor(Bernoulli, Int32, Int32)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli isGreaterThan, int a, int b)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan.
Int32	a	Constant value for a.
Int32	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_(isGreaterThan) p(isGreaterThan) factor(isGreaterThan,a,b)).

LogAverageFactor(Boolean, Discrete, Discrete)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool isGreaterThan, Discrete a, Discrete b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	a	Incoming message from a.
Discrete	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(isGreaterThan,a,b)).

LogAverageFactor(Boolean, Discrete, Int32)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool isGreaterThan, Discrete a, int b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	a	Incoming message from a.
Int32	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(isGreaterThan,a,b)).

LogAverageFactor(Boolean, Int32, Discrete)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool isGreaterThan, int a, Discrete b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	a	Constant value for a.
Discrete	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(isGreaterThan,a,b)).

LogAverageFactor(Boolean, Int32, Int32)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool isGreaterThan, int a, int b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	a	Constant value for a.
Int32	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(isGreaterThan,a,b)).

LogEvidenceRatio(Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(Bernoulli isGreaterThan)

Parameters

Type	Name	Description
Bernoulli	isGreaterThan	Incoming message from isGreaterThan.

Returns

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

Remarks

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

LogEvidenceRatio(Boolean, Discrete, Discrete)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool isGreaterThan, Discrete a, Discrete b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	a	Incoming message from a.
Discrete	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_(a,b) p(a,b) factor(isGreaterThan,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Discrete, Int32)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool isGreaterThan, Discrete a, int b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Discrete	a	Incoming message from a.
Int32	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(isGreaterThan,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Int32, Discrete)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool isGreaterThan, int a, Discrete b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	a	Constant value for a.
Discrete	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(isGreaterThan,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Int32, Int32)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool isGreaterThan, int a, int b)

Parameters

Type	Name	Description
Boolean	isGreaterThan	Constant value for isGreaterThan.
Int32	a	Constant value for a.
Int32	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(isGreaterThan,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.