public class MultivariateGaussianInverseGammaDistribution extends AbstractDistribution<Vector> implements ClosedFormDistribution<Vector>
Modifier and Type | Field and Description |
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static int |
DEFAULT_DIMENSIONALITY
Default dimensionality, 2.
|
protected MultivariateGaussian |
gaussian
Gaussian component
|
protected InverseGammaDistribution |
inverseGamma
Inverse-Gamma component
|
Constructor and Description |
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MultivariateGaussianInverseGammaDistribution()
Default constructor
|
MultivariateGaussianInverseGammaDistribution(int dimensionality)
Creates a new instance of MultivariateGaussianInverseGammaDistribution
|
MultivariateGaussianInverseGammaDistribution(MultivariateGaussian gaussian,
InverseGammaDistribution inverseGamma)
Creates a new instance of MultivariateGaussianInverseGammaDistribution
|
Modifier and Type | Method and Description |
---|---|
MultivariateGaussianInverseGammaDistribution |
clone()
This makes public the clone method on the
Object class and
removes the exception that it throws. |
void |
convertFromVector(Vector parameters)
Converts the object from a Vector of parameters.
|
Vector |
convertToVector()
Converts the object to a vector.
|
MultivariateGaussian |
getGaussian()
Getter for gaussian
|
InverseGammaDistribution |
getInverseGamma()
Getter for inverseGamma
|
Vector |
getMean()
Gets the arithmetic mean, or "first central moment" or "expectation",
of the distribution.
|
void |
sampleInto(java.util.Random random,
int sampleCount,
java.util.Collection<? super Vector> output)
Draws multiple random samples from the distribution and puts the result
into the given collection.
|
void |
setGaussian(MultivariateGaussian gaussian)
Setter for gaussian
|
void |
setInverseGamma(InverseGammaDistribution inverseGamma)
Setter for inverseGamma
|
sample, sample
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
sample, sample
public static final int DEFAULT_DIMENSIONALITY
protected MultivariateGaussian gaussian
protected InverseGammaDistribution inverseGamma
public MultivariateGaussianInverseGammaDistribution()
public MultivariateGaussianInverseGammaDistribution(int dimensionality)
dimensionality
- Dimensionality of the multivariate Gaussianpublic MultivariateGaussianInverseGammaDistribution(MultivariateGaussian gaussian, InverseGammaDistribution inverseGamma)
gaussian
- Gaussian componentinverseGamma
- Inverse-Gamma componentpublic MultivariateGaussianInverseGammaDistribution clone()
AbstractCloneableSerializable
Object
class and
removes the exception that it throws. Its default behavior is to
automatically create a clone of the exact type of object that the
clone is called on and to copy all primitives but to keep all references,
which means it is a shallow copy.
Extensions of this class may want to override this method (but call
super.clone()
to implement a "smart copy". That is, to target
the most common use case for creating a copy of the object. Because of
the default behavior being a shallow copy, extending classes only need
to handle fields that need to have a deeper copy (or those that need to
be reset). Some of the methods in ObjectUtil
may be helpful in
implementing a custom clone method.
Note: The contract of this method is that you must use
super.clone()
as the basis for your implementation.clone
in interface Vectorizable
clone
in interface CloneableSerializable
clone
in class AbstractCloneableSerializable
public Vector getMean()
DistributionWithMean
getMean
in interface DistributionWithMean<Vector>
public void sampleInto(java.util.Random random, int sampleCount, java.util.Collection<? super Vector> output)
Distribution
sampleInto
in interface Distribution<Vector>
random
- Random number generator to use.sampleCount
- The number of samples to draw. Cannot be negative.output
- The collection to add the samples into.public MultivariateGaussian getGaussian()
public void setGaussian(MultivariateGaussian gaussian)
gaussian
- Gaussian componentpublic InverseGammaDistribution getInverseGamma()
public void setInverseGamma(InverseGammaDistribution inverseGamma)
inverseGamma
- Inverse-Gamma componentpublic Vector convertToVector()
Vectorizable
convertToVector
in interface Vectorizable
public void convertFromVector(Vector parameters)
Vectorizable
convertFromVector
in interface Vectorizable
parameters
- The parameters to incorporate.