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

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

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

Creates a ExponentialDistribution from data

See Also:
Serialized Form

Constructor Summary
ExponentialDistribution.MaximumLikelihoodEstimator()
          Default estimator.
 
Method Summary
 ExponentialDistribution 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

ExponentialDistribution.MaximumLikelihoodEstimator

public ExponentialDistribution.MaximumLikelihoodEstimator()
Default estimator.

Method Detail

learn

public ExponentialDistribution 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>,ExponentialDistribution>
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.