gov.sandia.cognition.statistics.distribution

Class BinomialDistribution.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.BinomialDistribution

gov.sandia.cognition.statistics.distribution.BinomialDistribution.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,BinomialDistribution>, IntegerDistribution, ProbabilityFunction<java.lang.Number>, ProbabilityMassFunction<java.lang.Number>, UnivariateDistribution<java.lang.Number>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

BinomialDistribution

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

The Probability Mass Function of a binomial distribution.

See Also:

Serialized Form

Nested Class Summary

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

BinomialDistribution.CDF, BinomialDistribution.MaximumLikelihoodEstimator, BinomialDistribution.PMF

Field Summary

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

DEFAULT_N, DEFAULT_P

Constructor Summary

Constructors

Constructor and Description
PMF() Default constructor.
PMF(BinomialDistribution other) Copy constructor
PMF(int N, double p) Creates a new instance of PMF

Method Summary

Modifier and Type	Method and Description
static double	evaluate(int N, int k, double p) Returns the binomial CDF for the parameters N, k, p, which is the probability of exactly k successes in N experiments with expected per-trial success probability (Bernoulli) p
java.lang.Double	evaluate(java.lang.Number input) Returns the binomial PMF for the parameters N, k, p, which is the probability of exactly k successes in N experiments with expected per-trial success probability (Bernoulli) p
double	getEntropy() Gets the entropy of the values in the histogram.
BinomialDistribution.PMF	getProbabilityFunction() Gets the distribution function associated with this Distribution, either the PDF or PMF.
static double	logEvaluate(int N, int k, double p) Computes the natural logarithm of the PMF.
double	logEvaluate(java.lang.Number input) Evaluate the natural logarithm of the distribution function.

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

clone, convertFromVector, convertToVector, getCDF, getDomain, getDomainSize, getEstimator, getMaxSupport, getMean, getMeanAsDouble, getMinSupport, getN, getP, getVariance, sampleAsInt, sampleInto, sampleInto, setN, setP

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

sampleAsInts

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()

Default constructor.

PMF

public PMF(int N,
           double p)

Creates a new instance of PMF

Parameters:

N - Total number of experiments, must be greater than zero

p - Probability of a positive outcome (Bernoulli probability), [0,1]

PMF

public PMF(BinomialDistribution other)

Copy constructor

Parameters:

other - BinomialDistribution to copy

Method Detail

evaluate

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

Returns the binomial PMF for the parameters N, k, p, which is the probability of exactly k successes in N experiments with expected per-trial success probability (Bernoulli) p

Specified by:

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

Parameters:

input - Number of successes

Returns:

Probability of exactly input successes in N experiments with expected per-trial success probability (Bernoulli) p

evaluate

public static double evaluate(int N,
                              int k,
                              double p)

Returns the binomial CDF for the parameters N, k, p, which is the probability of exactly k successes in N experiments with expected per-trial success probability (Bernoulli) p

Parameters:

N - Total number of experiments

k - Total number of successes

p - Expected probability of success, Bernoulli parameter

Returns:

Probability of exactly k successes in N experiments with expected per-trial success probability (Bernoulli) p

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.

logEvaluate

public static double logEvaluate(int N,
                                 int k,
                                 double p)

Computes the natural logarithm of the PMF.

Parameters:

N - Total number of experiments

k - Total number of successes

p - Expected probability of success, Bernoulli parameter

Returns:

Computes the natural logarithm of the PMF.

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.

getProbabilityFunction

public BinomialDistribution.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 BinomialDistribution

Returns:

Distribution function associated with this Distribution.