Class UniformIntegerDistribution
- java.lang.Object
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- org.apache.commons.math3.distribution.AbstractIntegerDistribution
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- org.apache.commons.math3.distribution.UniformIntegerDistribution
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- All Implemented Interfaces:
java.io.Serializable
,IntegerDistribution
public class UniformIntegerDistribution extends AbstractIntegerDistribution
Implementation of the uniform integer distribution.- Since:
- 3.0
- See Also:
- Uniform distribution (discrete), at Wikipedia, Serialized Form
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Field Summary
Fields Modifier and Type Field Description private int
lower
Lower bound (inclusive) of this distribution.private static long
serialVersionUID
Serializable version identifier.private int
upper
Upper bound (inclusive) of this distribution.-
Fields inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution
random, randomData
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Constructor Summary
Constructors Constructor Description 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).
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
cumulativeProbability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(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 variableX
whose values are distributed according to this distribution, this method returnsP(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
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Field Detail
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serialVersionUID
private static final long serialVersionUID
Serializable version identifier.- See Also:
- Constant Field Values
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lower
private final int lower
Lower bound (inclusive) of this distribution.
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upper
private final int upper
Upper bound (inclusive) of this distribution.
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Constructor Detail
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UniformIntegerDistribution
public UniformIntegerDistribution(int lower, int upper) throws NumberIsTooLargeException
Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).Note: this constructor will implicitly create an instance of
Well19937c
as random generator to be used for sampling only (seesample()
andAbstractIntegerDistribution.sample(int)
). In case no sampling is needed for the created distribution, it is advised to passnull
as random generator via the appropriate constructors to avoid the additional initialisation overhead.- Parameters:
lower
- Lower bound (inclusive) of this distribution.upper
- Upper bound (inclusive) of this distribution.- Throws:
NumberIsTooLargeException
- iflower >= upper
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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
- iflower > upper
.- Since:
- 3.1
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Method Detail
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probability
public double probability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(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
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cumulativeProbability
public double cumulativeProbability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(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
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getNumericalMean
public double getNumericalMean()
Use this method to get the numerical value of the mean of this distribution. For lower boundlower
and upper boundupper
, the mean is0.5 * (lower + upper)
.- Returns:
- the mean or
Double.NaN
if it is not defined
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getNumericalVariance
public double getNumericalVariance()
Use this method to get the numerical value of the variance of this distribution. For lower boundlower
and upper boundupper
, andn = upper - lower + 1
, the variance is(n^2 - 1) / 12
.- Returns:
- the variance (possibly
Double.POSITIVE_INFINITY
orDouble.NaN
if it is not defined)
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getSupportLowerBound
public int getSupportLowerBound()
Access the lower bound of the support. This method must return the same value asinverseCumulativeProbability(0)
. In other words, this method must return
The lower bound of the support is equal to the lower bound parameter of the distribution.inf {x in Z | P(X <= x) > 0}
.- Returns:
- lower bound of the support
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getSupportUpperBound
public int getSupportUpperBound()
Access the upper bound of the support. This method must return the same value asinverseCumulativeProbability(1)
. In other words, this method must return
The upper bound of the support is equal to the upper bound parameter of the distribution.inf {x in R | P(X <= x) = 1}
.- Returns:
- upper bound of the support
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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
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sample
public int sample()
Generate a random value sampled from this distribution. The default implementation uses the inversion method.- Specified by:
sample
in interfaceIntegerDistribution
- Overrides:
sample
in classAbstractIntegerDistribution
- Returns:
- a random value
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