gov.sandia.cognition.statistics
Class AbstractDistribution<DataType>

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.statistics.AbstractDistribution<DataType>
Type Parameters:
DataType - Type of data that can be sampled from the Distribution.
All Implemented Interfaces:
Distribution<DataType>, CloneableSerializable, Serializable, Cloneable
Direct Known Subclasses:
AbstractClosedFormUnivariateDistribution, CategoricalDistribution, DirichletDistribution, InverseWishartDistribution, LinearMixtureModel, MaximumAPosterioriCategorizer, MultinomialDistribution, MultivariateGaussian, MultivariateGaussianInverseGammaDistribution, MultivariatePolyaDistribution, MultivariateStudentTDistribution, NormalInverseGammaDistribution, NormalInverseWishartDistribution

public abstract class AbstractDistribution<DataType>
extends AbstractCloneableSerializable
implements Distribution<DataType>

Partial implementation of Distribution.

Since:
3.0
Author:
Kevin R. Dixon
See Also:
Serialized Form

Constructor Summary
AbstractDistribution()
           
 
Method Summary
 DataType sample(Random random)
          Draws a single random sample from the distribution.
 
Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable
clone
 
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.Distribution
sample
 
Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable
clone
 

Constructor Detail

AbstractDistribution

public AbstractDistribution()
Method Detail

sample

public DataType sample(Random random)
Description copied from interface: Distribution
Draws a single random sample from the distribution.

Specified by:
sample in interface Distribution<DataType>
Parameters:
random - Random-number generator to use in order to generate random numbers.
Returns:
Sample drawn according to this distribution.