Class AbstractIntegerDistribution
- java.lang.Object
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- org.apache.commons.math.distribution.AbstractDistribution
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- org.apache.commons.math.distribution.AbstractIntegerDistribution
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- All Implemented Interfaces:
java.io.Serializable
,DiscreteDistribution
,Distribution
,IntegerDistribution
- Direct Known Subclasses:
BinomialDistributionImpl
,HypergeometricDistributionImpl
,PascalDistributionImpl
,PoissonDistributionImpl
,ZipfDistributionImpl
public abstract class AbstractIntegerDistribution extends AbstractDistribution implements IntegerDistribution, java.io.Serializable
Base class for integer-valued discrete distributions. Default implementations are provided for some of the methods that do not vary from distribution to distribution.- See Also:
- Serialized Form
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Method Summary
All Methods Instance Methods Abstract Methods Concrete Methods Modifier and Type Method 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
cumulativeProbability(double x0, double x1)
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).abstract double
cumulativeProbability(int x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).double
cumulativeProbability(int x0, int x1)
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).int
inverseCumulativeProbability(double p)
For a random variable X whose values are distributed according to this distribution, this method returns the largest x, such that P(X ≤ x) ≤p
.boolean
isSupportLowerBoundInclusive()
Use this method to get information about whether the lower bound of the support is inclusive or not.boolean
isSupportUpperBoundInclusive()
Use this method to get information about whether the upper bound of the support is inclusive or not.double
probability(double x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).void
reseedRandomGenerator(long seed)
Reseeds the random generator used to generate samples.int
sample()
Generates a random value sampled from this distribution.int[]
sample(int sampleSize)
Generates a random sample from the distribution.-
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.apache.commons.math.distribution.IntegerDistribution
probability
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Method Detail
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cumulativeProbability
public double cumulativeProbability(double x) throws MathException
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, or CDF, for this distribution.If
x
does not represent an integer value, the CDF is evaluated at the greatest integer less than x.- Specified by:
cumulativeProbability
in interfaceDistribution
- Parameters:
x
- the value at which the distribution function is evaluated.- Returns:
- cumulative probability that a random variable with this
distribution takes a value less than or equal to
x
- Throws:
MathException
- if the cumulative probability can not be computed due to convergence or other numerical errors.
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cumulativeProbability
public double cumulativeProbability(double x0, double x1) throws MathException
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).- Specified by:
cumulativeProbability
in interfaceDistribution
- Overrides:
cumulativeProbability
in classAbstractDistribution
- Parameters:
x0
- the (inclusive) lower boundx1
- the (inclusive) upper bound- Returns:
- the probability that a random variable with this distribution
will take a value between
x0
andx1
, including the endpoints. - Throws:
MathException
- if the cumulative probability can not be computed due to convergence or other numerical errors.java.lang.IllegalArgumentException
- ifx0 > x1
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cumulativeProbability
public abstract double cumulativeProbability(int x) throws MathException
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 distribution function, or PDF, for this distribution.- Specified by:
cumulativeProbability
in interfaceIntegerDistribution
- Parameters:
x
- the value at which the PDF is evaluated.- Returns:
- PDF for this distribution.
- Throws:
MathException
- if the cumulative probability can not be computed due to convergence or other numerical errors.
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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, or PMF, for the distribution.If
x
does not represent an integer value, 0 is returned.- Specified by:
probability
in interfaceDiscreteDistribution
- Parameters:
x
- the value at which the probability density function is evaluated- Returns:
- the value of the probability density function at x
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cumulativeProbability
public double cumulativeProbability(int x0, int x1) throws MathException
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).- Specified by:
cumulativeProbability
in interfaceIntegerDistribution
- Parameters:
x0
- the inclusive, lower boundx1
- the inclusive, upper bound- Returns:
- the cumulative probability.
- Throws:
MathException
- if the cumulative probability can not be computed due to convergence or other numerical errors.java.lang.IllegalArgumentException
- if x0 > x1
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inverseCumulativeProbability
public int inverseCumulativeProbability(double p) throws MathException
For a random variable X whose values are distributed according to this distribution, this method returns the largest x, such that P(X ≤ x) ≤p
.- Specified by:
inverseCumulativeProbability
in interfaceIntegerDistribution
- Parameters:
p
- the desired probability- Returns:
- the largest x such that P(X ≤ x) <= p
- Throws:
MathException
- if the inverse cumulative probability can not be computed due to convergence or other numerical errors.java.lang.IllegalArgumentException
- if p < 0 or p > 1
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reseedRandomGenerator
public void reseedRandomGenerator(long seed)
Reseeds the random generator used to generate samples.- Parameters:
seed
- the new seed- Since:
- 2.2
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sample
public int sample() throws MathException
Generates a random value sampled from this distribution. The default implementation uses the inversion method.- Returns:
- random value
- Throws:
MathException
- if an error occurs generating the random value- Since:
- 2.2
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sample
public int[] sample(int sampleSize) throws MathException
Generates a random sample from the distribution. The default implementation generates the sample by callingsample()
in a loop.- Parameters:
sampleSize
- number of random values to generate- Returns:
- an array representing the random sample
- Throws:
MathException
- if an error occurs generating the samplejava.lang.IllegalArgumentException
- if sampleSize is not positive- Since:
- 2.2
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isSupportLowerBoundInclusive
public boolean isSupportLowerBoundInclusive()
Use this method to get information about whether the lower bound of the support is inclusive or not. For discrete support, only true here is meaningful.- Returns:
- true (always but at Integer.MIN_VALUE because of the nature of discrete support)
- Since:
- 2.2
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isSupportUpperBoundInclusive
public boolean isSupportUpperBoundInclusive()
Use this method to get information about whether the upper bound of the support is inclusive or not. For discrete support, only true here is meaningful.- Returns:
- true (always but at Integer.MAX_VALUE because of the nature of discrete support)
- Since:
- 2.2
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