Class | Description |
---|---|
BinomialDistribution |
Class that models a binomial distribution
using the cern.jet.random library for binomial distributions.
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BivariateDistribution |
A Bivariate distribution is the abstraction of a distribution in two variables.
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BooleanDistribution |
A distribution with two mass points (named true and false)
in one variable.
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BoundedBinomialDistribution |
Class that models a bounded binomial distribution
using the cern.jet.random library for binomial distributions.
|
BoundedContinuousDistribution |
Abstraction that models continuous distributions that are cut off at certain bounds.
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BoundedDiscreteDistribution |
Abstraction that models discrete distributions that are cut off at certain bounds.
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BoundedUnivariateDistribution |
Abstraction to model a univariate distribution that has a lower and an upper bound.
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BurrDistribution |
Abstraction of the BurrDistributions within the COLT library.
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BurrDistribution10 |
Class to model the Burr type X distribution based on the COLT library.
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BurrDistribution12 |
Class to model the Burr type XII distribution based on the COLT library.
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BurrDistribution2 |
Class to model the Burr type II distribution based on the COLT library.
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BurrDistribution3 |
Class to model the Burr type III distribution based on the COLT library.
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BurrDistribution4 |
Class to model the Burr type IV distribution based on the COLT library.
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BurrDistribution5 |
Class to model the Burr type V distribution based on the COLT library.
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BurrDistribution6 |
Class to model the Burr type VI distribution based on the COLT library.
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BurrDistribution7 |
Class to model the Burr type VII distribution based on the COLT library.
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BurrDistribution8 |
Class to model the Burr type VIII distribution based on the COLT library.
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BurrDistribution9 |
Class to model the Burr type IX distribution based on the COLT library.
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CauchyDistribution |
Abstraction to represent a generalized CauchyDistribution.
|
COLTContinuousDistribution |
Abstraction for continuous distributions based on the COLT library.
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COLTDiscreteDistribution |
Abstraction for discrete distributions based on the COLT library.
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ContinuousDistribution |
Abstraction for continuous distributions based on the COLT library.
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ContinuousSpatialDistribution |
Distribution that describes how an entity will be situated spatially.
|
DiscreteDistribution |
Abstraction to describe a discrete distribution.
|
Distribution |
Abstraction to model a probability distribution.
|
DistributionFactory |
A class to generate instances of distributions used in the simulation.
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DummySpatialDistribution |
A spatial distribution that chooses an (evenly distributed) coordinate
within the rectangle if the spatial model is an instance of a RectangularSpatialModel),
and (0.0,0.0) if not.
|
ErlangDistribution |
Class to represent an Erlang distribution based on the COLT distribution library.
|
FiniteMassPointsDiscreteDistribution |
Class that models a distribution that has its mass concentrated in a finite number of points.
|
GeometricDistribution |
Class to model a geometric distribution based on the implementation in the COLT distribution library.
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LambdaDistribution |
Class to model a lambda distribution based on the implementation in the COLT distribution library.
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MultivariateDistribution |
Abstraction class to model distributions in several variables.
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MultivNormalDistribution |
Class to model a multivariate normal distribution using the multivariate normal distribution in the COLT library.
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NegativeBinomialDistribution |
Class to represent a negative binomial distribution based on the COLT library.
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NormDistribution |
Class that models a (univariate) normal distribution based on the math3.distribution library of the apache commons.
|
PoissonDistribution |
Class to model a poisson distribution using the COLT distribution library
with an average number of events k.
|
PowerlawDistribution |
Class that models a power law distribution (with cut off) based on the COLT library (see https://dst.lbl.gov/ACSSoftware/colt/api/cern/jet/random/Distributions.html#nextPowLaw(double,%20double,%20cern.jet.random.engine.RandomEngine))
Should return values following a power law (probably not exactly, since it does not asymptotically go to a power law, see https://en.wikipedia.org/wiki/Power_law#Power-law_probability_distributions)
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SpatialDistribution |
Abstraction to model distributions with values in (2 dimensional) space.
|
StandardCauchyDistribution |
Class that represents a standard Cauchy distribution (with a peak at 0 and scale parameter 1.0
(scale parameter is half-width at half maximum (HWHM)) based on the COLT library
Parameters can't be changed; for Cauchy distributions parameterized differently,
the reader is referred to other implementations or needs to implement their own distribution.
|
StandardLaplaceDistribution |
Class that realizes a standard Laplace distribution (double exponential distribution) L(0,1),
centered at 0 with scale parameter b=1.
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StandardLogisticDistribution |
Class that represents a standard logistic distribution (Log(0,1)), taken from the COLT library.
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StandardTriangularDistribution |
Class that represents a standard triangular distribution (in (-1,1)), taken from the COLT library.
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UniformContinuousDistribution |
Class that models a uniform distribution (thus is necessarily bounded).
|
UniformDiscreteDistribution |
Class to represent a distribution made of a finite number of mass points
of which each is as likely to be drawn than any other.
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UnivariateDistribution |
Abstraction for distributions in one variable.
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WeibullDistribution |
Class to model a Weibull distribution using the COLT distribution library.
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ZipfianDistribution |
Class to model a zipfian distribution based on the COLT library.
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