org.apache.commons.math3.distribution.AbstractIntegerDistribution

org.apache.commons.math3.distribution.EnumeratedIntegerDistribution

All Implemented Interfaces:: Serializable, IntegerDistribution

public class EnumeratedIntegerDistribution extends AbstractIntegerDistribution

Implementation of an integer-valued EnumeratedDistribution.

Values with zero-probability are allowed but they do not extend the support.
Duplicate values are allowed. Probabilities of duplicate values are combined when computing cumulative probabilities and statistics.

Since:

3.2

See Also:

Field Summary

Fields

Modifier and Type

Field

Description

protected final EnumeratedDistribution<Integer>

innerDistribution

EnumeratedDistribution instance (using the Integer wrapper) used to generate the pmf.

Fields inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution
random, randomData
Constructor Summary

Constructors

Constructor

Description

EnumeratedIntegerDistribution(int[] data)

Create a discrete integer-valued distribution from the input data.

EnumeratedIntegerDistribution(int[] singletons, double[] probabilities)

Create a discrete distribution using the given probability mass function definition.

EnumeratedIntegerDistribution(RandomGenerator rng, int[] data)

Create a discrete integer-valued distribution from the input data.

EnumeratedIntegerDistribution(RandomGenerator rng, int[] singletons, double[] probabilities)

Create a discrete distribution using the given random number generator and probability mass function definition.
Method Summary

Modifier and Type

Method

Description

double

cumulativeProbability(int x)

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

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.

int

getSupportLowerBound()

Access the lower bound of the support.

int

getSupportUpperBound()

Access the upper bound of the support.

boolean

isSupportConnected()

Use this method to get information about whether the support is connected, i.e.

double

probability(int x)

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

int

sample()

Generate a random value sampled from this distribution.

Methods inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution
cumulativeProbability, inverseCumulativeProbability, logProbability, reseedRandomGenerator, sample, solveInverseCumulativeProbability

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details
- innerDistribution
  
  protected final EnumeratedDistribution<Integer> innerDistribution
  
  EnumeratedDistribution instance (using the Integer wrapper) used to generate the pmf.
Constructor Details
- EnumeratedIntegerDistribution
  
  public EnumeratedIntegerDistribution(int[] singletons, double[] probabilities) throws DimensionMismatchException, NotPositiveException, MathArithmeticException, NotFiniteNumberException, NotANumberException
  
  Create a discrete distribution using the given probability mass function definition.
  Note: this constructor will implicitly create an instance of Well19937c as random generator to be used for sampling only (see sample() and AbstractIntegerDistribution.sample(int)). In case no sampling is needed for the created distribution, it is advised to pass null as random generator via the appropriate constructors to avoid the additional initialisation overhead.
  
  Parameters:
  
  singletons - array of random variable values.
  
  probabilities - array of probabilities.
  
  Throws:
  
  DimensionMismatchException - if singletons.length != probabilities.length
  
  NotPositiveException - if any of the probabilities are negative.
  
  NotFiniteNumberException - if any of the probabilities are infinite.
  
  NotANumberException - if any of the probabilities are NaN.
  
  MathArithmeticException - all of the probabilities are 0.
- EnumeratedIntegerDistribution
  
  public EnumeratedIntegerDistribution(RandomGenerator rng, int[] singletons, double[] probabilities) throws DimensionMismatchException, NotPositiveException, MathArithmeticException, NotFiniteNumberException, NotANumberException
  
  Create a discrete distribution using the given random number generator and probability mass function definition.
  
  Parameters:
  
  rng - random number generator.
  
  singletons - array of random variable values.
  
  probabilities - array of probabilities.
  
  Throws:
  
  DimensionMismatchException - if singletons.length != probabilities.length
  
  NotPositiveException - if any of the probabilities are negative.
  
  NotFiniteNumberException - if any of the probabilities are infinite.
  
  NotANumberException - if any of the probabilities are NaN.
  
  MathArithmeticException - all of the probabilities are 0.
- EnumeratedIntegerDistribution
  
  public EnumeratedIntegerDistribution(RandomGenerator rng, int[] data)
  
  Create a discrete integer-valued distribution from the input data. Values are assigned mass based on their frequency.
  
  Parameters:
  
  rng - random number generator used for sampling
  
  data - input dataset
  
  Since:
  
  3.6
- EnumeratedIntegerDistribution
  
  public EnumeratedIntegerDistribution(int[] data)
  
  Create a discrete integer-valued distribution from the input data. Values are assigned mass based on their frequency. For example, [0,1,1,2] as input creates a distribution with values 0, 1 and 2 having probability masses 0.25, 0.5 and 0.25 respectively,
  
  Parameters:
  
  data - input dataset
  
  Since:
  
  3.6
Method Details
- probability
  
  public double probability(int x)
  
  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 probability mass function (PMF) for the distribution.
  
  Parameters:
  
  x - the point at which the PMF is evaluated
  
  Returns:
  
  the value of the probability mass function at x
- cumulativeProbability
  
  public double cumulativeProbability(int x)
  
  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
- getNumericalMean
  
  public double getNumericalMean()
  
  Use this method to get the numerical value of the mean of this distribution.
  
  Returns:
  
  sum(singletons[i] * probabilities[i])
- getNumericalVariance
  
  public double getNumericalVariance()
  
  Use this method to get the numerical value of the variance of this distribution.
  
  Returns:
  
  sum((singletons[i] - mean) ^ 2 * probabilities[i])
- getSupportLowerBound
  
  public int 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 Z | P(X invalid input: '<'= x) > 0}.
  Returns the lowest value with non-zero probability.
  
  Returns:
  
  the lowest value with non-zero probability.
- getSupportUpperBound
  
  public int 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 invalid input: '<'= x) = 1}.
  Returns the highest value with non-zero probability.
  
  Returns:
  
  the highest value with non-zero probability.
- isSupportConnected
  
  public boolean isSupportConnected()
  
  Use this method to get information about whether the support is connected, i.e. whether all integers 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 int sample()
  
  Generate a random value sampled from this distribution. The default implementation uses the inversion method.
  
  Specified by:
  
  sample in interface IntegerDistribution
  
  Overrides:
  
  sample in class AbstractIntegerDistribution
  
  Returns:
  
  a random value

Class EnumeratedIntegerDistribution

Field Summary

Fields inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution

Constructor Summary

Method Summary

Methods inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution

Methods inherited from class java.lang.Object

Field Details

innerDistribution

Constructor Details

EnumeratedIntegerDistribution

EnumeratedIntegerDistribution

EnumeratedIntegerDistribution

EnumeratedIntegerDistribution

Method Details

probability

cumulativeProbability

getNumericalMean

getNumericalVariance

getSupportLowerBound

getSupportUpperBound

isSupportConnected

sample