gov.sandia.cognition.statistics.distribution

Class BinomialDistribution.CDF

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.CDF

All Implemented Interfaces:

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

Enclosing class:

BinomialDistribution

public static class BinomialDistribution.CDF
extends BinomialDistribution
implements ClosedFormCumulativeDistributionFunction<java.lang.Number>

CDF of the Binomial distribution, which is the probability of getting up to "x" successes in "N" trials with a Bernoulli probability of "p"

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
CDF() Default constructor.
CDF(BinomialDistribution other) Creates a new instance of CDF
CDF(int N, double p) Creates a new instance of BinomialDistribution

Method Summary

Modifier and Type	Method and Description
static double	evaluate(int N, int k, double p) Evaluates the CDF for integer values of x, N, and double p
java.lang.Double	evaluate(java.lang.Number input) Evaluates the function on the given input and returns the output.
BinomialDistribution.CDF	getCDF() Gets the CDF of a scalar distribution.

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

clone, convertFromVector, convertToVector, getDomain, getDomainSize, getEstimator, getMaxSupport, getMean, getMeanAsDouble, getMinSupport, getN, getP, getProbabilityFunction, 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.math.matrix.Vectorizable

clone, convertFromVector, convertToVector

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

getMaxSupport, getMeanAsDouble, getMinSupport, getVariance

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

getMean

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

sample, sample, sampleInto

Constructor Detail

CDF

public CDF()

Default constructor.

CDF

public CDF(int N,
           double p)

Creates a new instance of BinomialDistribution

Parameters:

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

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

CDF

public CDF(BinomialDistribution other)

Creates a new instance of CDF

Parameters:

other - Underlying Binomial PMF to use

Method Detail

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.

evaluate

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

Evaluates the CDF for integer values of x, N, and double p

Parameters:

k - Number of successful trials

N - Total number of possibilities in the distribution

p - Bernoulli probability of a positive experiment outcome

Returns:

Value of the Binomial CDF(N,n,p)

getCDF

public BinomialDistribution.CDF getCDF()

Description copied from interface: UnivariateDistribution

Gets the CDF of a scalar distribution.

Specified by:

getCDF in interface ClosedFormUnivariateDistribution<java.lang.Number>

Specified by:

getCDF in interface UnivariateDistribution<java.lang.Number>

Overrides:

getCDF in class BinomialDistribution

Returns:

CDF of the scalar distribution.