gov.sandia.cognition.statistics.distribution
Class PoissonDistribution.WeightedMaximumLikelihoodEstimator

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

public static class PoissonDistribution.WeightedMaximumLikelihoodEstimator
extends AbstractCloneableSerializable
implements DistributionWeightedEstimator<Number,PoissonDistribution>

Creates a PoissonDistribution from weighted data.

Since:
3.3.3
See Also:
Serialized Form

Constructor Summary
PoissonDistribution.WeightedMaximumLikelihoodEstimator()
          Creates a new WeightedMaximumLikelihoodEstimator.
 
Method Summary
 PoissonDistribution.PMF learn(Collection<? extends WeightedValue<? extends Number>> data)
          Creates a new instance of PoissonDistribution using a weighted Maximum Likelihood estimate based on the given data.
 
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

PoissonDistribution.WeightedMaximumLikelihoodEstimator

public PoissonDistribution.WeightedMaximumLikelihoodEstimator()
Creates a new WeightedMaximumLikelihoodEstimator.

Method Detail

learn

public PoissonDistribution.PMF learn(Collection<? extends WeightedValue<? extends Number>> data)
Creates a new instance of PoissonDistribution using a weighted Maximum Likelihood estimate based on the given data.

Specified by:
learn in interface BatchLearner<Collection<? extends WeightedValue<? extends Number>>,PoissonDistribution>
Parameters:
data - Weighed pairs of data (first is data, second is weight) that was generated by some unknown PoissonDistribution distribution.
Returns:
Maximum Likelihood PoissonDistribution that generated the data.