gov.sandia.cognition.statistics.distribution

Class StudentTDistribution.MaximumLikelihoodEstimator

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.distribution.StudentTDistribution.MaximumLikelihoodEstimator

All Implemented Interfaces:

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

Enclosing class:

StudentTDistribution

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

Estimates the parameters of the Student-t distribution from the given data, where the degrees of freedom are estimated from the Kurtosis of the sample data.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_VARIANCE Typical value of a defaultVariance, 1.0E-5

Constructor Summary

Constructors

Constructor and Description
MaximumLikelihoodEstimator() Default constructor
MaximumLikelihoodEstimator(double defaultVariance) Creates a new instance of MaximumLikelihoodEstimator

Method Summary

Modifier and Type	Method and Description
StudentTDistribution	learn(java.util.Collection<? extends java.lang.Double> data) Creates a new instance of UnivariateGaussian from the given data
static StudentTDistribution.PDF	learn(java.util.Collection<? extends java.lang.Double> data, double defaultVariance) Creates a new instance of UnivariateGaussian from 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

Field Detail

DEFAULT_VARIANCE

public static final double DEFAULT_VARIANCE

Typical value of a defaultVariance, 1.0E-5

See Also:

Constant Field Values

Constructor Detail

MaximumLikelihoodEstimator

public MaximumLikelihoodEstimator()

Default constructor

MaximumLikelihoodEstimator

public MaximumLikelihoodEstimator(double defaultVariance)

Creates a new instance of MaximumLikelihoodEstimator

Parameters:

defaultVariance - Amount to add to the variance to keep it from being 0.0

Method Detail

learn

public StudentTDistribution learn(java.util.Collection<? extends java.lang.Double> data)

Creates a new instance of UnivariateGaussian from the given data

Specified by:

learn in interface BatchLearner<java.util.Collection<? extends java.lang.Double>,StudentTDistribution>

Parameters:

data - Data to fit a UnivariateGaussian against

Returns:

Maximum likelihood estimate of the UnivariateGaussian that generated the data

learn

public static StudentTDistribution.PDF learn(java.util.Collection<? extends java.lang.Double> data,
                                             double defaultVariance)

Creates a new instance of UnivariateGaussian from the given data

Parameters:

data - Data to fit a UnivariateGaussian against

defaultVariance - Amount to add to the variance to keep it from being 0.0

Returns:

Maximum likelihood estimate of the UnivariateGaussian that generated the data