gov.sandia.cognition.statistics.distribution

Class UnivariateGaussian.MaximumLikelihoodEstimator

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.distribution.UnivariateGaussian.MaximumLikelihoodEstimator

All Implemented Interfaces:

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

Enclosing class:

UnivariateGaussian

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

Creates a UnivariateGaussian from 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
double	getDefaultVariance() Gets the default variance, which is the amount added to the variance.
UnivariateGaussian.PDF	learn(java.util.Collection<? extends java.lang.Double> data) Creates a new instance of UnivariateGaussian from the given data
static UnivariateGaussian.PDF	learn(java.util.Collection<? extends java.lang.Number> data, double defaultVariance) Creates a new instance of UnivariateGaussian from the given data
void	setDefaultVariance(double defaultVariance) Sets the default variance, which is the amount added to the variance.

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 UnivariateGaussian.PDF 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>,UnivariateGaussian.PDF>

Parameters:

data - Data to fit a UnivariateGaussian against

Returns:

Maximum likelihood estimate of the UnivariateGaussian that generated the data

learn

public static UnivariateGaussian.PDF learn(java.util.Collection<? extends java.lang.Number> 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

getDefaultVariance

public double getDefaultVariance()

Gets the default variance, which is the amount added to the variance. If this is greater than zero, it avoids creating zero variance.

Returns:

The default variance. Cannot be negative.

setDefaultVariance

public void setDefaultVariance(double defaultVariance)

Sets the default variance, which is the amount added to the variance. If this is greater than zero, it avoids creating zero variance.

Parameters:

defaultVariance - The default variance. Cannot be negative.