Cognitoware.Robotics.dll

Class GaussianMoment<X>

System.Object

Cognitoware.Mathematics.Probability.RandomDistribution<X>

Cognitoware.Mathematics.Probability.Continuous.GaussianMoment<X>

Represents a Gaussian distribution using a mean and covariance.

GaussianMoment(GaussianCanonical)

Creates a Gaussian from the canonical parameterization.

GaussianMoment(Double, Double)

Creates a single dimension Gaussian distribution with the specified mean and variance.

GaussianMoment(X, Matrix)

Creates a multivariate Gaussian distribution with the specified mean and variance.

AliasAs()

Inherited from Cognitoware.Mathematics.Probability.RandomDistribution

Equals(Object)

Inherited from System.Object

Finalize()

Inherited from System.Object

Fn(Vector, Vector, Matrix)

Calculates the value at result for a Gaussian with the specified mean and covariance.

Fn(Double, Double, Double)

Calculates the value at result for a Gaussian with the specified mean and covariance.

GetEntropy(IEnumerable<X>)

Inherited from Cognitoware.Mathematics.Probability.RandomDistribution

GetHashCode()

Inherited from System.Object

GetType()

Inherited from System.Object

MemberwiseClone()

Inherited from System.Object

Multiply(GaussianMoment<X>, GaussianMoment<X>)

Takes the product of two Gaussians.

Returns the probability of result in the Gaussian.

Product(GaussianMoment<X>)

Takes the product of two Gaussians.

Sample(Random)

ToString()

Writes the mean and covariance to a string.

Represents a Gaussian distribution using a mean and covariance.

public GaussianMoment(GaussianCanonical x)

Creates a Gaussian from the canonical parameterization.

`x`

- The Gaussian represented with the canonical parameterization.public GaussianMoment(Double mean, Double variance)

Creates a single dimension Gaussian distribution with the specified mean and variance.

`mean`

- The mean of the Gaussian.`variance`

- The variance of the Gaussian.public GaussianMoment(X mean, Matrix variance)

Creates a multivariate Gaussian distribution with the specified mean and variance.

`mean`

- The mean of the Gaussian.`variance`

- The variance of the Gaussian.public static Double Fn(Vector x, Vector mean, Matrix covariance)

Calculates the value at result for a Gaussian with the specified mean and covariance.

`x`

- The value whose probability is calculated.`mean`

- The mean of the Gaussian used to calculate the probability.`covariance`

- The variance of the Gaussian used to calculate the probability.The probability of result.

public static Double Fn(Double x, Double mean, Double variance)

Calculates the value at result for a Gaussian with the specified mean and covariance.

`x`

- The value whose probability is calculated.`mean`

- The mean of the Gaussian used to calculate the probability.`variance`

- The variance of the Gaussian used to calculate the probability.The probability of result.

public static GaussianMoment<X> Multiply(GaussianMoment<X> a0, GaussianMoment<X> a1)

Takes the product of two Gaussians.

`a0`

- The left operand.`a1`

- The right operand.A new Gaussian that incorporate evidence from the two operands.

public override Double ProbabilityOf(X x)

Returns the probability of result in the Gaussian.

`x`

- The value whose probability is returned.The probability of result.

public final virtual GaussianMoment<X> Product(GaussianMoment<X> that)

Takes the product of two Gaussians.

`that`

- The second operand.A new Gaussian that incorporate evidence from the two operands.

public override X Sample(Random select)

public override String ToString()

Writes the mean and covariance to a string.

A string representing the Gaussian.