Cognitoware.Robotics.dll
Class GaussianMoment<X>
X: The type of the random value.
Implemented Interfaces
Summary
Represents a Gaussian distribution using a mean and covariance.
Constructor Summary
Creates a Gaussian from the canonical parameterization.
Creates a single dimension Gaussian distribution with the specified mean and variance.
Creates a multivariate Gaussian distribution with the specified mean and variance.
Method Summary
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.
Takes the product of two Gaussians.
Writes the mean and covariance to a string.
Details
Represents a Gaussian distribution using a mean and covariance.
Constructor Details
public GaussianMoment(GaussianCanonical x)
Creates a Gaussian from the canonical parameterization.
Parameters:
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.
Parameters:
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.
Parameters:
mean - The mean of the Gaussian.
variance - The variance of the Gaussian.
Method Details
public static Double Fn(Vector x, Vector mean, Matrix covariance)
Calculates the value at result for a Gaussian with the specified mean and covariance.
Parameters:
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.
Returns:
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.
Parameters:
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.
Returns:
The probability of result.
public static GaussianMoment<X> Multiply(GaussianMoment<X> a0, GaussianMoment<X> a1)
Takes the product of two Gaussians.
Parameters:
a0 - The left operand.
a1 - The right operand.
Returns:
A new Gaussian that incorporate evidence from the two operands.
public override Double ProbabilityOf(X x)
Returns the probability of result in the Gaussian.
Parameters:
x - The value whose probability is returned.
Returns:
The probability of result.
public final virtual GaussianMoment<X> Product(GaussianMoment<X> that)
Takes the product of two Gaussians.
Parameters:
that - The second operand.
Returns:
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.
Returns:
A string representing the Gaussian.