EnumeratedRealDistribution (Apache Commons Math 3.6.1 API)

java.lang.Object
- org.apache.commons.math3.distribution.AbstractRealDistribution
- - org.apache.commons.math3.distribution.EnumeratedRealDistribution

All Implemented Interfaces:

Serializable, RealDistribution
```
public class EnumeratedRealDistribution
extends AbstractRealDistribution
```
Implementation of a real-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:
Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

protected EnumeratedDistribution<Double> innerDistribution
EnumeratedDistribution (using the Double wrapper) used to generate the pmf.
- Fields inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution
  random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY

Fields
Modifier and Type	Field and Description
`protected EnumeratedDistribution<Double>`	`innerDistribution` `EnumeratedDistribution` (using the `Double` wrapper) used to generate the pmf.

Constructor Summary

Constructors
Constructor and Description
`EnumeratedRealDistribution(double[] data)` Create a discrete real-valued distribution from the input data.
`EnumeratedRealDistribution(double[] singletons, double[] probabilities)` Create a discrete real-valued distribution using the given probability mass function enumeration.
`EnumeratedRealDistribution(RandomGenerator rng, double[] data)` Create a discrete real-valued distribution from the input data.
`EnumeratedRealDistribution(RandomGenerator rng, double[] singletons, double[] probabilities)` Create a discrete real-valued distribution using the given random number generator and probability mass function enumeration.

Method Summary

Methods
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`	`density(double 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.
`double`	`getSupportLowerBound()` Access the lower bound of the support.
`double`	`getSupportUpperBound()` Access the upper bound of the support.
`double`	`inverseCumulativeProbability(double p)` Computes the quantile function of this distribution.
`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(double x)` For a random variable `X` whose values are distributed according to this distribution, this method returns `P(X = x)`.
`double`	`sample()` Generate a random value sampled from this distribution.

Methods inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution
cumulativeProbability, getSolverAbsoluteAccuracy, logDensity, probability, reseedRandomGenerator, sample

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

- Field Detail
  - innerDistribution
```
protected final EnumeratedDistribution<Double> innerDistribution
```
    EnumeratedDistribution (using the Double wrapper) used to generate the pmf.
- Constructor Detail
  - EnumeratedRealDistribution
```
public EnumeratedRealDistribution(double[] singletons,
                          double[] probabilities)
                           throws DimensionMismatchException,
                                  NotPositiveException,
                                  MathArithmeticException,
                                  NotFiniteNumberException,
                                  NotANumberException
```
    Create a discrete real-valued distribution using the given probability mass function enumeration.
    Note: this constructor will implicitly create an instance of Well19937c as random generator to be used for sampling only (see sample() and AbstractRealDistribution.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.
  - EnumeratedRealDistribution
```
public EnumeratedRealDistribution(RandomGenerator rng,
                          double[] singletons,
                          double[] probabilities)
                           throws DimensionMismatchException,
                                  NotPositiveException,
                                  MathArithmeticException,
                                  NotFiniteNumberException,
                                  NotANumberException
```
    Create a discrete real-valued distribution using the given random number generator and probability mass function enumeration.
    
    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.
  - EnumeratedRealDistribution
```
public EnumeratedRealDistribution(RandomGenerator rng,
                          double[] data)
```
    Create a discrete real-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
  - EnumeratedRealDistribution
```
public EnumeratedRealDistribution(double[] data)
```
    Create a discrete real-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 Detail
  - probability
```
public double probability(double 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.
    
    Specified by:
    
    probability in interface RealDistribution
    
    Overrides:
    
    probability in class AbstractRealDistribution
    
    Parameters:
    x - the point at which the PMF is evaluated
    
    Returns:
    zero.
  - density
```
public double density(double 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 point x
  - cumulativeProbability
```
public double cumulativeProbability(double 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
  - inverseCumulativeProbability
```
public double inverseCumulativeProbability(double p)
                                    throws OutOfRangeException
```
    Computes the quantile function of this distribution. For a random variable X distributed according to this distribution, the returned value is
    - inf{x in R | P(X<=x) >= p} for 0 < p <= 1,
    - inf{x in R | P(X<=x) > 0} for p = 0.
    The default implementation returns
    - RealDistribution.getSupportLowerBound() for p = 0,
    - RealDistribution.getSupportUpperBound() for p = 1.
    Specified by:
    
    inverseCumulativeProbability in interface RealDistribution
    
    Overrides:
    
    inverseCumulativeProbability in class AbstractRealDistribution
    
    Parameters:
    p - the cumulative probability
    
    Returns:
    the smallest p-quantile of this distribution (largest 0-quantile for p = 0)
    
    Throws:
    
    OutOfRangeException - if p < 0 or p > 1
  - 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 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}.
    Returns the lowest value with non-zero probability.
    
    Returns:
    the lowest value with non-zero probability.
  - 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}.
    Returns the highest value with non-zero probability.
    
    Returns:
    the highest value with non-zero probability.
  - isSupportLowerBoundInclusive
```
public boolean isSupportLowerBoundInclusive()
```
    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. The support of this distribution includes the lower bound.
    
    Returns:
    true
  - isSupportUpperBoundInclusive
```
public boolean isSupportUpperBoundInclusive()
```
    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. The support of this distribution includes the upper bound.
    
    Returns:
    true
  - 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 double sample()
```
    Generate a random value sampled from this distribution. The default implementation uses the inversion method.
    
    Specified by:
    
    sample in interface RealDistribution
    
    Overrides:
    
    sample in class AbstractRealDistribution
    
    Returns:
    a random value.

Class EnumeratedRealDistribution

Field Summary

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

Constructor Summary

Method Summary

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

Methods inherited from class java.lang.Object

Field Detail

innerDistribution

Constructor Detail

EnumeratedRealDistribution

EnumeratedRealDistribution

EnumeratedRealDistribution

EnumeratedRealDistribution

Method Detail

probability

density

cumulativeProbability

inverseCumulativeProbability

getNumericalMean

getNumericalVariance

getSupportLowerBound

getSupportUpperBound

isSupportLowerBoundInclusive

isSupportUpperBoundInclusive

isSupportConnected

sample