org.nd4j.linalg.api.rng.distribution.impl

Class BinomialDistribution

java.lang.Object

org.nd4j.linalg.api.rng.distribution.BaseDistribution

org.nd4j.linalg.api.rng.distribution.impl.BinomialDistribution

All Implemented Interfaces:

Distribution

public class BinomialDistribution
extends BaseDistribution

Base distribution derived from apache commons math http://commons.apache.org/proper/commons-math/

(specifically the org.apache.commons.math3.distribution.BinomialDistribution

Author:

Adam Gibson

Field Summary

Fields inherited from class org.nd4j.linalg.api.rng.distribution.BaseDistribution

random, solverAbsoluteAccuracy

Constructor Summary

Constructors

Constructor and Description
BinomialDistribution(int trials, double p) Create a binomial distribution with the given number of trials and probability of success.
BinomialDistribution(int n, INDArray p)
BinomialDistribution(Random rng, int trials, double p) Creates a binomial distribution.

Method Summary

Modifier and Type	Method and Description
double	cumulativeProbability(double x) For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x).
double	cumulativeProbability(double x0, double x1) For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
double	cumulativeProbability(int x)
double	density(double x) Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
int	getNumberOfTrials() Access the number of trials for this distribution.
double	getNumericalMean() Use this method to get the numerical value of the mean of this distribution.
double	getNumericalVariance() Use this method to get the numerical value of the variance of this distribution.
double	getProbabilityOfSuccess() Access the probability of success for this distribution.
double	getSupportLowerBound() Access the lower bound of the support.
double	getSupportUpperBound() Access the upper bound of the support.
boolean	isSupportConnected() Use this method to get information about whether the support is connected, i.e.
boolean	isSupportLowerBoundInclusive() Whether or not the lower bound of support is in the domain of the density function.
boolean	isSupportUpperBoundInclusive() Whether or not the upper bound of support is in the domain of the density function.
double	probability(int x)
INDArray	sample(int[] shape) Sample the given shape

Methods inherited from class org.nd4j.linalg.api.rng.distribution.BaseDistribution

getSolverAbsoluteAccuracy, inverseCumulativeProbability, probability, probability, reseedRandomGenerator, sample, sample

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

BinomialDistribution

public BinomialDistribution(int trials,
                            double p)

Create a binomial distribution with the given number of trials and probability of success.

Parameters:

trials - Number of trials.

p - Probability of success.

Throws:

org.apache.commons.math3.exception.NotPositiveException - if trials < 0.

org.apache.commons.math3.exception.OutOfRangeException - if p < 0 or p > 1.

BinomialDistribution

public BinomialDistribution(Random rng,
                            int trials,
                            double p)

Creates a binomial distribution.

Parameters:

rng - Random number generator.

trials - Number of trials.

p - Probability of success.

Throws:

org.apache.commons.math3.exception.NotPositiveException - if trials < 0.

org.apache.commons.math3.exception.OutOfRangeException - if p < 0 or p > 1.

Since:

3.1

BinomialDistribution

public BinomialDistribution(int n,
                            INDArray p)

Method Detail

getNumberOfTrials

public int getNumberOfTrials()

Access the number of trials for this distribution.

Returns:

the number of trials.

getProbabilityOfSuccess

public double getProbabilityOfSuccess()

Access the probability of success for this distribution.

Returns:

the probability of success.

probability

public double probability(int x)

cumulativeProbability

public double cumulativeProbability(int x)

density

public double density(double x)

Description copied from interface: Distribution

Returns the probability density function (PDF) of this distribution evaluated at the specified point x. In general, the PDF is the derivative of the CDF. If the derivative does not exist at x, then an appropriate replacement should be returned, e.g. Double.POSITIVE_INFINITY, Double.NaN, or the limit inferior or limit superior of the difference quotient.

Parameters:

x - the point at which the PDF is evaluated

Returns:

the value of the probability density function at point x

cumulativeProbability

public double cumulativeProbability(double x)

Description copied from interface: Distribution

For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x). In other words, this method represents the (cumulative) distribution function (CDF) for this distribution.

Parameters:

x - the point at which the CDF is evaluated

Returns:

the probability that a random variable with this distribution takes a value less than or equal to x

cumulativeProbability

public double cumulativeProbability(double x0,
                                    double x1)
                             throws org.apache.commons.math3.exception.NumberIsTooLargeException

Description copied from interface: Distribution

For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).

Parameters:

x0 - the exclusive lower bound

x1 - the inclusive upper bound

Returns:

the probability that a random variable with this distribution takes a value between x0 and x1, excluding the lower and including the upper endpoint

Throws:

org.apache.commons.math3.exception.NumberIsTooLargeException - if x0 > x1

getNumericalMean

public double getNumericalMean()

Use this method to get the numerical value of the mean of this distribution.

For n trials and probability parameter p, the mean is n * p.

Returns:

the mean or Double.NaN if it is not defined

getNumericalVariance

public double getNumericalVariance()

Use this method to get the numerical value of the variance of this distribution.

For n trials and probability parameter p, the variance is n * p * (1 - p).

Returns:

the variance (possibly Double.POSITIVE_INFINITY as for certain cases in org.apache.commons.math3.distribution.TDistribution) or Double.NaN if it is not defined

getSupportLowerBound

public double getSupportLowerBound()

Access the lower bound of the support. This method must return the same value as inverseCumulativeProbability(0). In other words, this method must return

inf {x in R | P(X <= x) > 0}.

The lower bound of the support is always 0 except for the probability parameter p = 1.

Returns:

lower bound of the support (0 or the number of trials)

getSupportUpperBound

public double getSupportUpperBound()

Access the upper bound of the support. This method must return the same value as inverseCumulativeProbability(1). In other words, this method must return

inf {x in R | P(X <= x) = 1}.

The upper bound of the support is the number of trials except for the probability parameter p = 0.

Returns:

upper bound of the support (number of trials or 0)

isSupportLowerBoundInclusive

public boolean isSupportLowerBoundInclusive()

Description copied from interface: Distribution

Whether or not the lower bound of support is in the domain of the density function. Returns true iff getSupporLowerBound() is finite and density(getSupportLowerBound()) returns a non-NaN, non-infinite value.

Returns:

true if the lower bound of support is finite and the density function returns a non-NaN, non-infinite value there

isSupportUpperBoundInclusive

public boolean isSupportUpperBoundInclusive()

Description copied from interface: Distribution

Whether or not the upper bound of support is in the domain of the density function. Returns true iff getSupportUpperBound() is finite and density(getSupportUpperBound()) returns a non-NaN, non-infinite value.

Returns:

true if the upper bound of support is finite and the density function returns a non-NaN, non-infinite value there

isSupportConnected

public boolean isSupportConnected()

Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support.

The support of this distribution is connected.

Returns:

true

sample

public INDArray sample(int[] shape)

Description copied from interface: Distribution

Sample the given shape

Specified by:

sample in interface Distribution

Overrides:

sample in class BaseDistribution

Parameters:

shape - the given shape

Returns:

an ndarray with random samples from this distribution