gov.sandia.cognition.statistics.distribution
Class BetaDistribution.WeightedMomentMatchingEstimator

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.statistics.distribution.BetaDistribution.WeightedMomentMatchingEstimator
All Implemented Interfaces:
BatchLearner<Collection<? extends WeightedValue<? extends Double>>,BetaDistribution>, DistributionWeightedEstimator<Double,BetaDistribution>, CloneableSerializable, Serializable, Cloneable
Enclosing class:
BetaDistribution

@PublicationReference(author={"Andrew Gelman","John B. Carlin","Hal S. Stern","Donald B. Rubin"},
                      title="Bayesian Data Analysis, Second Edition",
                      type=Book,
                      year=2004,
                      pages=582,
                      notes="Equation A.3")
public static class BetaDistribution.WeightedMomentMatchingEstimator
extends AbstractCloneableSerializable
implements DistributionWeightedEstimator<Double,BetaDistribution>

Estimates the parameters of a Beta distribution using the matching of moments, not maximum likelihood.

See Also:
Serialized Form

Constructor Summary
BetaDistribution.WeightedMomentMatchingEstimator()
          Default constructor
 
Method Summary
 BetaDistribution learn(Collection<? extends WeightedValue<? extends Double>> data)
          The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.
 
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.util.CloneableSerializable
clone
 

Constructor Detail

BetaDistribution.WeightedMomentMatchingEstimator

public BetaDistribution.WeightedMomentMatchingEstimator()
Default constructor

Method Detail

learn

public BetaDistribution learn(Collection<? extends WeightedValue<? extends Double>> data)
Description copied from interface: BatchLearner
The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.

Specified by:
learn in interface BatchLearner<Collection<? extends WeightedValue<? extends Double>>,BetaDistribution>
Parameters:
data - The data that the learning algorithm will use to create an object of ResultType.
Returns:
The object that is created based on the given data using the learning algorithm.