gov.sandia.cognition.statistics.distribution

Class CategoricalDistribution.PMF

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

gov.sandia.cognition.statistics.distribution.CategoricalDistribution

gov.sandia.cognition.statistics.distribution.CategoricalDistribution.PMF

All Implemented Interfaces:

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

Enclosing class:

CategoricalDistribution

public static class CategoricalDistribution.PMF
extends CategoricalDistribution
implements ProbabilityMassFunction<Vector>, VectorInputEvaluator<Vector,java.lang.Double>

PMF of the Categorical Distribution

See Also:

Serialized Form

Nested Class Summary

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

CategoricalDistribution.PMF

Field Summary

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

DEFAULT_NUM_CLASSES, parameters

Constructor Summary

Constructors

Constructor and Description
PMF() Creates a new instance of CategoricalDistribution
PMF(CategoricalDistribution other) Copy constructor
PMF(int numClasses) Creates a new instance of CategoricalDistribution
PMF(Vector parameters) Creates a new instance of CategoricalDistribution

Method Summary

Modifier and Type	Method and Description
java.lang.Double	evaluate(Vector input) Evaluates the function on the given input and returns the output.
double	getEntropy() Gets the entropy of the values in the histogram.
CategoricalDistribution.PMF	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.CategoricalDistribution

clone, convertFromVector, convertToVector, getDomain, getDomainSize, getInputDimensionality, getMean, getParameters, sampleInto, setParameters

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.DiscreteDistribution

getDomain, getDomainSize

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

sample, sample, sampleInto

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

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

getInputDimensionality

Constructor Detail

PMF

public PMF()

Creates a new instance of CategoricalDistribution

PMF

public PMF(int numClasses)

Creates a new instance of CategoricalDistribution

Parameters:

numClasses - Number of classes (labels or parameters) to use.

PMF

public PMF(Vector parameters)

Creates a new instance of CategoricalDistribution

Parameters:

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

PMF

public PMF(CategoricalDistribution other)

Copy constructor

Parameters:

other - CategoricalDistribution to copy

Method Detail

getEntropy

public double getEntropy()

Description copied from interface: ProbabilityMassFunction

Gets the entropy of the values in the histogram.

Specified by:

getEntropy in interface ProbabilityMassFunction<Vector>

Returns:

The entropy of the values in the histogram.

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.

evaluate

public java.lang.Double evaluate(Vector input)

Description copied from interface: Evaluator

Evaluates the function on the given input and returns the output.

Specified by:

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

Parameters:

input - The input to evaluate.

Returns:

The output produced by evaluating the input.

getProbabilityFunction

public CategoricalDistribution.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<Vector>

Specified by:

getProbabilityFunction in interface DiscreteDistribution<Vector>

Specified by:

getProbabilityFunction in interface ProbabilityMassFunction<Vector>

Overrides:

getProbabilityFunction in class CategoricalDistribution

Returns:

Distribution function associated with this Distribution.