Class GaussianProductVmpOp

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

Inheritance

Object

GaussianProductVmpOp

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), "Product", new Type[]{typeof(double), typeof(double)})]
[Quality(QualityBand.Mature)]
public static class GaussianProductVmpOp

Methods

AAverageLogarithm(Gaussian, Gaussian)

VMP message to a.

Declaration

public static Gaussian AAverageLogarithm(Gaussian Product, Gaussian B)

Parameters

Type	Name	Description
Gaussian	Product	Incoming message from product. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	B	Incoming message from b. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Gaussian	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, product is integrated out before taking the logarithm. The formula is exp(sum_(b) p(b) log(sum_product p(product) factor(product,a,b))).

Exceptions

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

AAverageLogarithm(Gaussian, Double)

VMP message to a.

Declaration

public static Gaussian AAverageLogarithm(Gaussian Product, double B)

Parameters

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

Returns

Type	Description
Gaussian	The outgoing VMP message to the a argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	Product is not a proper distribution.

AAverageLogarithm(Double, Gaussian)

VMP message to a.

Declaration

[NotSupported("Variational Message Passing does not support a Product factor with fixed output and two random inputs.")]
public static Gaussian AAverageLogarithm(double Product, Gaussian B)

Parameters

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

Returns

Type	Description
Gaussian	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(product,a,b))).

Exceptions

Type	Condition
ImproperMessageException	B is not a proper distribution.

AAverageLogarithm(Double, Double)

VMP message to a.

Declaration

public static Gaussian AAverageLogarithm(double Product, double B)

Parameters

Type	Name	Description
Double	Product	Constant value for product.
Double	B	Constant value for b.

Returns

Type	Description
Gaussian	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.

AverageLogFactor(Gaussian)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(Gaussian product)

Parameters

Type	Name	Description
Gaussian	product	Incoming message from product.

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.

BAverageLogarithm(Gaussian, Gaussian)

VMP message to b.

Declaration

public static Gaussian BAverageLogarithm(Gaussian Product, Gaussian A)

Parameters

Type	Name	Description
Gaussian	Product	Incoming message from product. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	A	Incoming message from a. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Gaussian	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, product is integrated out before taking the logarithm. The formula is exp(sum_(a) p(a) log(sum_product p(product) factor(product,a,b))).

Exceptions

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

BAverageLogarithm(Gaussian, Double)

VMP message to b.

Declaration

public static Gaussian BAverageLogarithm(Gaussian Product, double A)

Parameters

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

Returns

Type	Description
Gaussian	The outgoing VMP message to the b argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	Product is not a proper distribution.

BAverageLogarithm(Double, Gaussian)

VMP message to b.

Declaration

[NotSupported("Variational Message Passing does not support a Product factor with fixed output and two random inputs.")]
public static Gaussian BAverageLogarithm(double Product, Gaussian A)

Parameters

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

Returns

Type	Description
Gaussian	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(product,a,b))).

Exceptions

Type	Condition
ImproperMessageException	A is not a proper distribution.

BAverageLogarithm(Double, Double)

VMP message to b.

Declaration

public static Gaussian BAverageLogarithm(double Product, double A)

Parameters

Type	Name	Description
Double	Product	Constant value for product.
Double	A	Constant value for a.

Returns

Type	Description
Gaussian	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.

ProductAverageLogarithm(Gaussian, Gaussian)

VMP message to product.

Declaration

public static Gaussian ProductAverageLogarithm(Gaussian A, Gaussian B)

Parameters

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

Returns

Type	Description
Gaussian	The outgoing VMP message to the product argument.

Remarks

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

Exceptions

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

ProductAverageLogarithm(Gaussian, Double)

VMP message to product.

Declaration

public static Gaussian ProductAverageLogarithm(Gaussian A, double B)

Parameters

Type	Name	Description
Gaussian	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
Gaussian	The outgoing VMP message to the product argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	A is not a proper distribution.

ProductAverageLogarithm(TruncatedGaussian, Double)

VMP message to product.

Declaration

public static TruncatedGaussian ProductAverageLogarithm(TruncatedGaussian A, double B)

Parameters

Type	Name	Description
TruncatedGaussian	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
TruncatedGaussian	The outgoing VMP message to the product argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	A is not a proper distribution.

ProductAverageLogarithm(Double, Gaussian)

VMP message to product.

Declaration

public static Gaussian ProductAverageLogarithm(double A, Gaussian B)

Parameters

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

Returns

Type	Description
Gaussian	The outgoing VMP message to the product argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	B is not a proper distribution.

ProductAverageLogarithm(Double, TruncatedGaussian)

VMP message to product.

Declaration

public static TruncatedGaussian ProductAverageLogarithm(double A, TruncatedGaussian B)

Parameters

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

Returns

Type	Description
TruncatedGaussian	The outgoing VMP message to the product argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	B is not a proper distribution.

ProductDeriv(Gaussian, Gaussian, Gaussian, Gaussian, Gaussian)

Declaration

public static Gaussian ProductDeriv(Gaussian Product, Gaussian A, Gaussian B, Gaussian to_A, Gaussian to_B)

Parameters

Type	Name	Description
Gaussian	Product
Gaussian	A
Gaussian	B
Gaussian	to_A
Gaussian	to_B

Returns

Type	Description
Gaussian

ProductDeriv(Gaussian, Gaussian, Double, Gaussian)

Declaration

public static Gaussian ProductDeriv(Gaussian Product, Gaussian A, double B, Gaussian to_A)

Parameters

Type	Name	Description
Gaussian	Product
Gaussian	A
Double	B
Gaussian	to_A

Returns

Type	Description
Gaussian

ProductDeriv(Gaussian, Double, Gaussian, Gaussian)

Declaration

public static Gaussian ProductDeriv(Gaussian Product, double A, Gaussian B, Gaussian to_B)

Parameters

Type	Name	Description
Gaussian	Product
Double	A
Gaussian	B
Gaussian	to_B

Returns

Type	Description
Gaussian