org.apache.commons.statistics.distribution

Class UniformDiscreteDistribution

• java.lang.Object
• org.apache.commons.statistics.distribution.UniformDiscreteDistribution

• Nested classes/interfaces inherited from interface org.apache.commons.statistics.distribution.DiscreteDistribution

DiscreteDistribution.Sampler
• Constructor Summary

Constructors
Constructor and Description
UniformDiscreteDistribution(int lower, int upper)
Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
• Constructor Detail

• UniformDiscreteDistribution

public UniformDiscreteDistribution(int lower,
int upper)
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:
IllegalArgumentException - if lower > upper.
• 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 - 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 - 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.
• getMean

public double getMean()
Gets 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.
• getVariance

public double getVariance()
Gets 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, or Double.NaN if it is not defined.
• getSupportLowerBound

public int getSupportLowerBound()
Gets the lower bound of the support. This method must return the same value as inverseCumulativeProbability(0), i.e. inf {x in Z | P(X <= x) > 0}. By convention, Integer.MIN_VALUE should be substituted for negative infinity. 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()
Gets the upper bound of the support. This method must return the same value as inverseCumulativeProbability(1), i.e. inf {x in R | P(X <= x) = 1}. By convention, Integer.MAX_VALUE should be substituted for positive infinity. 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()
Indicates 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
• probability

public double probability(int x0,
int x1)
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1). The default implementation uses the identity P(x0 < X <= x1) = P(X <= x1) - P(X <= x0)
Specified by:
probability in interface DiscreteDistribution
Parameters:
x0 - Lower bound (exclusive).
x1 - Upper bound (inclusive).
Returns:
the probability that a random variable with this distribution will take a value between x0 and x1, excluding the lower and including the upper endpoint.
• sample

public static int[] sample(int n,
DiscreteDistribution.Sampler sampler)
Utility function for allocating an array and filling it with n samples generated by the given sampler.
Parameters:
n - Number of samples.
sampler - Sampler.
Returns:
an array of size n.