gov.sandia.cognition.statistics.distribution

Class UniformIntegerDistribution.PMF

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

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

gov.sandia.cognition.statistics.AbstractClosedFormIntegerDistribution

gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution

gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.PMF

All Implemented Interfaces:

Evaluator<java.lang.Number,java.lang.Double>, Vectorizable, ClosedFormComputableDistribution<java.lang.Number>, ClosedFormDiscreteUnivariateDistribution<java.lang.Number>, ClosedFormDistribution<java.lang.Number>, ClosedFormUnivariateDistribution<java.lang.Number>, ComputableDistribution<java.lang.Number>, DiscreteDistribution<java.lang.Number>, Distribution<java.lang.Number>, DistributionWithMean<java.lang.Number>, EstimableDistribution<java.lang.Number,UniformIntegerDistribution>, IntegerDistribution, ProbabilityFunction<java.lang.Number>, ProbabilityMassFunction<java.lang.Number>, UnivariateDistribution<java.lang.Number>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

UniformIntegerDistribution

public static class UniformIntegerDistribution.PMF
extends UniformIntegerDistribution
implements ProbabilityMassFunction<java.lang.Number>

Probability mass function of a discrete uniform distribution.

See Also:

Serialized Form

Nested Class Summary

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

UniformIntegerDistribution.CDF, UniformIntegerDistribution.MaximumLikelihoodEstimator, UniformIntegerDistribution.PMF

Field Summary

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

DEFAULT_MAX_SUPPORT, DEFAULT_MIN_SUPPORT

Constructor Summary

Constructors

Constructor and Description
PMF() Creates a new UniformIntegerDistribution.PMF with min and max 0.
PMF(int minSupport, int maxSupport) Creates a new UniformIntegerDistribution.PMF with the given min and max.
PMF(UniformIntegerDistribution other) Creates a new UniformIntegerDistribution.PMF as a copy of the given other uniform distribution.

Method Summary

Modifier and Type	Method and Description
static double	evaluate(int input, int minSupport, int maxSupport) Evaluates the probability mass function of the discrete uniform distribution.
java.lang.Double	evaluate(java.lang.Number input) Evaluates the function on the given input and returns the output.
double	evaluateAsDouble(int input) Evaluates the input value for the PMF to compute its mass as a double.
double	getEntropy() Gets the entropy of the values in the histogram.
UniformIntegerDistribution.PMF	getProbabilityFunction() Gets the distribution function associated with this Distribution, either the PDF or PMF.
static double	logEvaluate(int input, int minSupport, int maxSupport) Evaluates the log of the probability mass function of the discrete uniform distribution.
double	logEvaluate(java.lang.Number input) Evaluate the natural logarithm of the distribution function.

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

clone, convertFromVector, convertToVector, getCDF, getDomain, getDomainSize, getEstimator, getMaxSupport, getMean, getMeanAsDouble, getMinSupport, getVariance, sampleAsInt, sampleInto, setMaxSupport, setMinSupport

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

sampleAsInts, sampleInto

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

Constructor Detail

PMF

public PMF()

Creates a new UniformIntegerDistribution.PMF with min and max 0.

PMF

public PMF(int minSupport,
           int maxSupport)

Creates a new UniformIntegerDistribution.PMF with the given min and max.

Parameters:

minSupport - The minimum support. Should be less-than-or-equal to the max support.

maxSupport - The maximum support. Should be greater-than-or-equal to the min support.

PMF

public PMF(UniformIntegerDistribution other)

Creates a new UniformIntegerDistribution.PMF as a copy of the given other uniform distribution.

Parameters:

other - The other distribution.

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<java.lang.Number>

Returns:

The entropy of the values in the histogram.

logEvaluate

public double logEvaluate(java.lang.Number 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<java.lang.Number>

Parameters:

input - The input to be evaluated

Returns:

Natural logarithm of the distribution function.

evaluate

public java.lang.Double evaluate(java.lang.Number input)

Description copied from interface: Evaluator

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

Specified by:

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

Parameters:

input - The input to evaluate.

Returns:

The output produced by evaluating the input.

evaluateAsDouble

public double evaluateAsDouble(int input)

Evaluates the input value for the PMF to compute its mass as a double.

Parameters:

input - The input value.

Returns:

The probability mass for the input value.

evaluate

public static double evaluate(int input,
                              int minSupport,
                              int maxSupport)

Evaluates the probability mass function of the discrete uniform distribution. The mass is a uniform value if the input is between the supports (inclusive) and 0 if it is not.

Parameters:

input - The input value.

minSupport - The minimum support. Should be less-than-or-equal to the max support.

maxSupport - The maximum support. Should be greater-than-or-equal to the min support.

Returns:

The probability mass value for the input.

logEvaluate

public static double logEvaluate(int input,
                                 int minSupport,
                                 int maxSupport)

Evaluates the log of the probability mass function of the discrete uniform distribution. The mass is a uniform value if the input is between the supports (inclusive) and 0 if it is not.

Parameters:

input - The input value.

minSupport - The minimum support. Should be less-than-or-equal to the max support.

maxSupport - The maximum support. Should be greater-than-or-equal to the min support.

Returns:

The log of the probability mass value for the input.

getProbabilityFunction

public UniformIntegerDistribution.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.Number>

Specified by:

getProbabilityFunction in interface DiscreteDistribution<java.lang.Number>

Specified by:

getProbabilityFunction in interface ProbabilityMassFunction<java.lang.Number>

Overrides:

getProbabilityFunction in class UniformIntegerDistribution

Returns:

Distribution function associated with this Distribution.