gov.sandia.cognition.statistics.distribution
Class LaplaceDistribution.MaximumLikelihoodEstimator

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

public static class LaplaceDistribution.MaximumLikelihoodEstimator
extends AbstractCloneableSerializable
implements DistributionEstimator<Double,LaplaceDistribution>

Estimates the ML parameters of a Laplace distribution from a Collection of Numbers.

See Also:
Serialized Form

Constructor Summary
LaplaceDistribution.MaximumLikelihoodEstimator()
          Default constructor
 
Method Summary
 LaplaceDistribution learn(Collection<? 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

LaplaceDistribution.MaximumLikelihoodEstimator

public LaplaceDistribution.MaximumLikelihoodEstimator()
Default constructor

Method Detail

learn

public LaplaceDistribution learn(Collection<? 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 Double>,LaplaceDistribution>
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.