gov.sandia.cognition.statistics.distribution
Class NormalInverseWishartDistribution.PDF

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.statistics.AbstractDistribution<Matrix>
          extended by gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
              extended by gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution.PDF
All Implemented Interfaces:
Evaluator<Matrix,Double>, Vectorizable, ClosedFormComputableDistribution<Matrix>, ClosedFormDistribution<Matrix>, ComputableDistribution<Matrix>, Distribution<Matrix>, DistributionWithMean<Matrix>, ProbabilityDensityFunction<Matrix>, ProbabilityFunction<Matrix>, CloneableSerializable, Serializable, Cloneable
Enclosing class:
NormalInverseWishartDistribution

public static class NormalInverseWishartDistribution.PDF
extends NormalInverseWishartDistribution
implements ProbabilityDensityFunction<Matrix>

PDF of the normal inverse-Wishart distribution.

See Also:
Serialized Form

Nested Class Summary
 
Nested classes/interfaces inherited from class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
NormalInverseWishartDistribution.PDF
 
Field Summary
 
Fields inherited from class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
covarianceDivisor, DEFAULT_COVARIANCE_DIVISOR, DEFAULT_DIMENSIONALITY, gaussian, inverseWishart
 
Constructor Summary
NormalInverseWishartDistribution.PDF()
          Default constructor
NormalInverseWishartDistribution.PDF(int dimensionality, double covarianceDivisor)
          Creates a new instance of NormalInverseWishartDistribution
NormalInverseWishartDistribution.PDF(MultivariateGaussian gaussian, InverseWishartDistribution inverseWishart, double covarianceDivisor)
          Creates a new instance of NormalInverseWishartDistribution
NormalInverseWishartDistribution.PDF(NormalInverseWishartDistribution other)
          Copy constructor
 
Method Summary
 Double evaluate(Matrix input)
          Evaluates the function on the given input and returns the output.
 NormalInverseWishartDistribution.PDF getProbabilityFunction()
          Gets the distribution function associated with this Distribution, either the PDF or PMF.
 double logEvaluate(Matrix input)
          Evaluate the natural logarithm of the distribution function.
 
Methods inherited from class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution
clone, convertFromVector, convertToVector, getCovarianceDivisor, getGaussian, getInputDimensionality, getInverseWishart, getMean, sample, setCovarianceDivisor, setGaussian, setInverseWishart
 
Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution
sample
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface gov.sandia.cognition.statistics.DistributionWithMean
getMean
 
Methods inherited from interface gov.sandia.cognition.math.matrix.Vectorizable
clone, convertFromVector, convertToVector
 
Methods inherited from interface gov.sandia.cognition.statistics.Distribution
sample, sample
 

Constructor Detail

NormalInverseWishartDistribution.PDF

public NormalInverseWishartDistribution.PDF()
Default constructor


NormalInverseWishartDistribution.PDF

public NormalInverseWishartDistribution.PDF(int dimensionality,
                                            double covarianceDivisor)
Creates a new instance of NormalInverseWishartDistribution

Parameters:
dimensionality - Dimensionality of the distributions
covarianceDivisor - Term that divides the covariance sampled from the inverseWishart, must be greater than zero.

NormalInverseWishartDistribution.PDF

public NormalInverseWishartDistribution.PDF(MultivariateGaussian gaussian,
                                            InverseWishartDistribution inverseWishart,
                                            double covarianceDivisor)
Creates a new instance of NormalInverseWishartDistribution

Parameters:
gaussian - Generates the mean, given the covariance from the inverseWishart.
inverseWishart - Generates the covariance for the Gaussian.
covarianceDivisor - Term that divides the covariance sampled from the inverseWishart, must be greater than zero.

NormalInverseWishartDistribution.PDF

public NormalInverseWishartDistribution.PDF(NormalInverseWishartDistribution other)
Copy constructor

Parameters:
other - NormalInverseWishartDistribution to copy
Method Detail

getProbabilityFunction

public NormalInverseWishartDistribution.PDF getProbabilityFunction()
Description copied from interface: ComputableDistribution
Gets the distribution function associated with this Distribution, either the PDF or PMF.

Specified by:
getProbabilityFunction in interface ComputableDistribution<Matrix>
Specified by:
getProbabilityFunction in interface ProbabilityDensityFunction<Matrix>
Overrides:
getProbabilityFunction in class NormalInverseWishartDistribution
Returns:
Distribution function associated with this Distribution.

logEvaluate

public double logEvaluate(Matrix input)
Description copied from interface: ProbabilityFunction
Evaluate the natural logarithm of the distribution function. This is sometimes more efficient than evaluating the distribution function itself, and when evaluating the product of many independent or exchangeable samples.

Specified by:
logEvaluate in interface ProbabilityFunction<Matrix>
Returns:
Natural logarithm of the distribution function.

evaluate

public Double evaluate(Matrix input)
Description copied from interface: Evaluator
Evaluates the function on the given input and returns the output.

Specified by:
evaluate in interface Evaluator<Matrix,Double>
Parameters:
input - The input to evaluate.
Returns:
The output produced by evaluating the input.