gov.sandia.cognition.statistics.distribution

Class ExponentialDistribution.MaximumLikelihoodEstimator

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

All Implemented Interfaces:

BatchLearner<java.util.Collection<? extends java.lang.Double>,ExponentialDistribution>, DistributionEstimator<java.lang.Double,ExponentialDistribution>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

ExponentialDistribution

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

Creates a ExponentialDistribution from data

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MaximumLikelihoodEstimator() Default estimator.

Method Summary

Modifier and Type	Method and Description
ExponentialDistribution	learn(java.util.Collection<? extends java.lang.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

MaximumLikelihoodEstimator

public MaximumLikelihoodEstimator()

Default estimator.

Method Detail

learn

public ExponentialDistribution learn(java.util.Collection<? extends java.lang.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<java.util.Collection<? extends java.lang.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.