gov.sandia.cognition.statistics.distribution

Class DirichletDistribution.PDF

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

gov.sandia.cognition.statistics.distribution.DirichletDistribution

gov.sandia.cognition.statistics.distribution.DirichletDistribution.PDF

All Implemented Interfaces:

Evaluator<Vector,java.lang.Double>, VectorInputEvaluator<Vector,java.lang.Double>, Vectorizable, ClosedFormComputableDistribution<Vector>, ClosedFormDistribution<Vector>, ComputableDistribution<Vector>, Distribution<Vector>, DistributionWithMean<Vector>, ProbabilityDensityFunction<Vector>, ProbabilityFunction<Vector>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

DirichletDistribution

public static class DirichletDistribution.PDF
extends DirichletDistribution
implements ProbabilityDensityFunction<Vector>, VectorInputEvaluator<Vector,java.lang.Double>

PDF of the Dirichlet distribution.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class gov.sandia.cognition.statistics.distribution.DirichletDistribution

DirichletDistribution.PDF

Field Summary

Fields inherited from class gov.sandia.cognition.statistics.distribution.DirichletDistribution

parameters

Constructor Summary

Constructors

Constructor and Description
PDF() Default constructor.
PDF(DirichletDistribution other) Copy Constructor.
PDF(Vector parameters) Creates a new instance of PDF

Method Summary

Modifier and Type	Method and Description
java.lang.Double	evaluate(Vector input) Evaluates the Dirichlet PDF about the given input.
int	getInputDimensionality() Gets the expected dimensionality of the input vector to the evaluator, if it is known.
DirichletDistribution.PDF	getProbabilityFunction() Gets the distribution function associated with this Distribution, either the PDF or PMF.
double	logEvaluate(Vector input) Evaluate the natural logarithm of the distribution function.

Methods inherited from class gov.sandia.cognition.statistics.distribution.DirichletDistribution

clone, convertFromVector, convertToVector, getMean, getParameters, sample, sampleInto, setParameters

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

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.DistributionWithMean

getMean

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

clone, convertFromVector, convertToVector

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

sample, sample, sampleInto

Constructor Detail

PDF

public PDF()

Default constructor.

PDF

public PDF(Vector parameters)

Creates a new instance of PDF

Parameters:

parameters - Parameters of the Dirichlet distribution, must be at least 2-dimensional and each element must be positive.

PDF

public PDF(DirichletDistribution other)

Copy Constructor.

Parameters:

other - DirichletDistribution to copy.

Method Detail

evaluate

public java.lang.Double evaluate(Vector input)

Evaluates the Dirichlet PDF about the given input. Note that we normalize the given input by its L1 norm to ensure that its entries sum to 1.

Specified by:

evaluate in interface Evaluator<Vector,java.lang.Double>

Parameters:

input - Input to consider, automatically normalized by its L1 norm without side-effect.

Returns:

Dirichlet PDF evaluated about the given (unnormalized) input.

logEvaluate

public double logEvaluate(Vector input)

Description copied from interface: ProbabilityFunction

Evaluate the natural logarithm of the distribution function. This is sometimes more efficient than evaluating the distribution function itself, and when evaluating the product of many independent or exchangeable samples.

Specified by:

logEvaluate in interface ProbabilityFunction<Vector>

Parameters:

input - The input to be evaluated

Returns:

Natural logarithm of the distribution function.

getInputDimensionality

public int getInputDimensionality()

Description copied from interface: VectorInputEvaluator

Gets the expected dimensionality of the input vector to the evaluator, if it is known. If it is not known, -1 is returned.

Specified by:

getInputDimensionality in interface VectorInputEvaluator<Vector,java.lang.Double>

Returns:

The expected dimensionality of the input vector to the evaluator, or -1 if it is not known.

getProbabilityFunction

public DirichletDistribution.PDF 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<Vector>

Specified by:

getProbabilityFunction in interface ProbabilityDensityFunction<Vector>

Overrides:

getProbabilityFunction in class DirichletDistribution

Returns:

Distribution function associated with this Distribution.