gov.sandia.cognition.statistics.distribution

Class DeterministicDistribution

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.AbstractDistribution<NumberType>

gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution<java.lang.Double>

gov.sandia.cognition.statistics.distribution.DeterministicDistribution

All Implemented Interfaces:

Vectorizable, ClosedFormComputableDistribution<java.lang.Double>, ClosedFormDiscreteUnivariateDistribution<java.lang.Double>, ClosedFormDistribution<java.lang.Double>, ClosedFormUnivariateDistribution<java.lang.Double>, ComputableDistribution<java.lang.Double>, DiscreteDistribution<java.lang.Double>, Distribution<java.lang.Double>, DistributionWithMean<java.lang.Double>, UnivariateDistribution<java.lang.Double>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

DeterministicDistribution.CDF, DeterministicDistribution.PMF

@PublicationReference(author="Wikipedia",
                      title="Degenerate distribution",
                      type=WebPage,
                      year=2009,
                      url="http://en.wikipedia.org/wiki/Degenerate_distribution")
public class DeterministicDistribution
extends AbstractClosedFormUnivariateDistribution<java.lang.Double>
implements ClosedFormDiscreteUnivariateDistribution<java.lang.Double>

A deterministic distribution that returns samples at a single point. This is also known as a degenerate distribution.

Since:

3.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DeterministicDistribution.CDF CDF of the deterministic distribution.
static class	DeterministicDistribution.PMF PMF of the deterministic distribution.

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_POINT Default point, 0.0

Constructor Summary

Constructors

Constructor and Description
DeterministicDistribution() Creates a new instance of DeterministicDistribution
DeterministicDistribution(DeterministicDistribution other) Copy Constructor
DeterministicDistribution(double point) Creates a new instance of DeterministicDistribution

Method Summary

Modifier and Type	Method and Description
void	convertFromVector(Vector parameters) Converts the object from a Vector of parameters.
Vector	convertToVector() Converts the object to a vector.
DeterministicDistribution.CDF	getCDF() Gets the CDF of a scalar distribution.
java.util.Set<java.lang.Double>	getDomain() Returns an object that allows an iteration through the domain (x-axis, independent variable) of the Distribution
int	getDomainSize() Gets the size of the domain.
java.lang.Double	getMaxSupport() Gets the minimum support (domain or input) of the distribution.
java.lang.Double	getMean() Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.
double	getMeanAsDouble() Gets the mean of the distribution as a double.
java.lang.Double	getMinSupport() Gets the minimum support (domain or input) of the distribution.
double	getPoint() Getter for point
DeterministicDistribution.PMF	getProbabilityFunction() Gets the distribution function associated with this Distribution, either the PDF or PMF.
double	getVariance() Gets the variance of the distribution.
void	sampleInto(java.util.Random random, int sampleCount, java.util.Collection<? super java.lang.Double> output) Draws multiple random samples from the distribution and puts the result into the given collection.
void	setPoint(double point) Setter for point

Methods inherited from class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution

clone

Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution

sample, sample

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.statistics.Distribution

sample, sample

Methods inherited from interface gov.sandia.cognition.math.matrix.Vectorizable

clone

Field Detail

DEFAULT_POINT

public static final double DEFAULT_POINT

Default point, 0.0

See Also:

Constant Field Values

Constructor Detail

DeterministicDistribution

public DeterministicDistribution()

Creates a new instance of DeterministicDistribution

DeterministicDistribution

public DeterministicDistribution(double point)

Creates a new instance of DeterministicDistribution

Parameters:

point - Location of the distribution

DeterministicDistribution

public DeterministicDistribution(DeterministicDistribution other)

Copy Constructor

Parameters:

other - DeterministicDistribution to copy

Method Detail

getPoint

public double getPoint()

Getter for point

Returns:

Location of the distribution

setPoint

public void setPoint(double point)

Setter for point

Parameters:

point - Location of the distribution

getMean

public java.lang.Double getMean()

Description copied from interface: DistributionWithMean

Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.

Specified by:

getMean in interface DistributionWithMean<java.lang.Double>

Returns:

Mean of the distribution.

getMeanAsDouble

public double getMeanAsDouble()

Description copied from interface: UnivariateDistribution

Gets the mean of the distribution as a double.

Specified by:

getMeanAsDouble in interface UnivariateDistribution<java.lang.Double>

Returns:

The mean as a double.

sampleInto

public void sampleInto(java.util.Random random,
                       int sampleCount,
                       java.util.Collection<? super java.lang.Double> output)

Description copied from interface: Distribution

Draws multiple random samples from the distribution and puts the result into the given collection.

Specified by:

sampleInto in interface Distribution<java.lang.Double>

Parameters:

random - Random number generator to use.

sampleCount - The number of samples to draw. Cannot be negative.

output - The collection to add the samples into.

convertToVector

public Vector convertToVector()

Description copied from interface: Vectorizable

Converts the object to a vector.

Specified by:

convertToVector in interface Vectorizable

Returns:

The Vector form of the object.

convertFromVector

public void convertFromVector(Vector parameters)

Description copied from interface: Vectorizable

Converts the object from a Vector of parameters.

Specified by:

convertFromVector in interface Vectorizable

Parameters:

parameters - The parameters to incorporate.

getVariance

public double getVariance()

Description copied from interface: UnivariateDistribution

Gets the variance of the distribution. This is sometimes called the second central moment by more pedantic people, which is equivalent to the square of the standard deviation.

Specified by:

getVariance in interface UnivariateDistribution<java.lang.Double>

Returns:

Variance of the distribution.

getCDF

public DeterministicDistribution.CDF getCDF()

Description copied from interface: UnivariateDistribution

Gets the CDF of a scalar distribution.

Specified by:

getCDF in interface ClosedFormUnivariateDistribution<java.lang.Double>

Specified by:

getCDF in interface UnivariateDistribution<java.lang.Double>

Returns:

CDF of the scalar distribution.

getMinSupport

public java.lang.Double getMinSupport()

Description copied from interface: UnivariateDistribution

Gets the minimum support (domain or input) of the distribution.

Specified by:

getMinSupport in interface UnivariateDistribution<java.lang.Double>

Returns:

Minimum support.

getMaxSupport

public java.lang.Double getMaxSupport()

Description copied from interface: UnivariateDistribution

Gets the minimum support (domain or input) of the distribution.

Specified by:

getMaxSupport in interface UnivariateDistribution<java.lang.Double>

Returns:

Minimum support.

getDomain

public java.util.Set<java.lang.Double> getDomain()

Description copied from interface: DiscreteDistribution

Returns an object that allows an iteration through the domain (x-axis, independent variable) of the Distribution

Specified by:

getDomain in interface DiscreteDistribution<java.lang.Double>

Returns:

Collection that enumerates each value that the domain can take

getDomainSize

public int getDomainSize()

Description copied from interface: DiscreteDistribution

Gets the size of the domain.

Specified by:

getDomainSize in interface DiscreteDistribution<java.lang.Double>

Returns:

The size of the domain.

getProbabilityFunction

public DeterministicDistribution.PMF getProbabilityFunction()

Description copied from interface: ComputableDistribution

Gets the distribution function associated with this Distribution, either the PDF or PMF.

Specified by:

getProbabilityFunction in interface ComputableDistribution<java.lang.Double>

Specified by:

getProbabilityFunction in interface DiscreteDistribution<java.lang.Double>

Returns:

Distribution function associated with this Distribution.