org.apache.commons.math3.distribution
Class UniformIntegerDistribution

java.lang.Object
  extended by org.apache.commons.math3.distribution.AbstractIntegerDistribution
      extended by org.apache.commons.math3.distribution.UniformIntegerDistribution
All Implemented Interfaces:
Serializable, IntegerDistribution

public class UniformIntegerDistribution
extends AbstractIntegerDistribution

Implementation of the uniform integer distribution.

Since:
3.0
Version:
$Id: UniformIntegerDistribution.java 7721 2013-02-14 14:07:13Z CardosoP $
See Also:
Uniform distribution (discrete), at Wikipedia, Serialized Form

Field Summary
 
Fields inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution
random, randomData
 
Constructor Summary
UniformIntegerDistribution(int lower, int upper)
          Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
UniformIntegerDistribution(RandomGenerator rng, int lower, int upper)
          Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
 
Method Summary
 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, reseedRandomGenerator, sample, solveInverseCumulativeProbability
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

UniformIntegerDistribution

public UniformIntegerDistribution(int lower,
                                  int upper)
                           throws NumberIsTooLargeException
Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).

Parameters:
lower - Lower bound (inclusive) of this distribution.
upper - Upper bound (inclusive) of this distribution.
Throws:
NumberIsTooLargeException - if lower >= upper.

UniformIntegerDistribution

public UniformIntegerDistribution(RandomGenerator rng,
                                  int lower,
                                  int upper)
                           throws NumberIsTooLargeException
Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).

Parameters:
rng - Random number generator.
lower - Lower bound (inclusive) of this distribution.
upper - Upper bound (inclusive) of this distribution.
Throws:
NumberIsTooLargeException - if lower >= upper.
Since:
3.1
Method Detail

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. For lower bound lower and upper bound upper, the mean is 0.5 * (lower + upper).

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 lower bound lower and upper bound upper, and n = upper - lower + 1, the variance is (n^2 - 1) / 12.

Returns:
the variance (possibly Double.POSITIVE_INFINITY or Double.NaN if it is not defined)

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 <= x) > 0}.

The lower bound of the support is equal to the lower bound parameter of the distribution.

Returns:
lower bound of the support

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 <= x) = 1}.

The upper bound of the support is equal to the upper bound parameter of the distribution.

Returns:
upper bound of the support

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


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