Package random

package random

Random number generation for the JSIM simulation engine. The package provides the engines, the continuous and discrete probability distributions and the distribution parameters used to characterize service and inter-arrival times.

Related Packages

Package	Description
random.discrete	Discrete probability distributions for the JSIM simulation engine (Bernoulli, binomial, geometric, Poisson, uniform, ...).
random.engine	Random number generator engines (including the Mersenne Twister) underlying the JMT distribution classes.

Class	Description
AbstractDistribution	Base class of the JMT probability distributions, defining the common random drawing interface.
AbstractParameter	TODO rivedere la descrizione interface for all distributions parameters.
Batch	This is the Batched distribution.
BatchPar	This is the parameter that should be passed to the Batched distribution.
Burst	This is the Burst distribution.
BurstPar	This is the parameter that should be passed to the Burst distribution.
CoxianDistr	This is the Coxian distribution.
CoxianPar	This is the parameter that should be passed to the Coxian distribution.
DeterministicDistr	This is the Deterministic distribution, which returns always the same value contained in the parameter.
DeterministicDistrPar	This is the parameter that should be passed to the Deterministic distribution.
Distribution	This is the Distribution abstract class, which is the interface of all distributions.
DistributionContainer	Title:Distribution Container
Empirical	This is the Empirical distribution, which is constructed with data provided by the user.
EmpiricalEntry	Class used for the empirical distribution, through which the user provides the data needed to construct the empirical distribution: for each empirical entry the requested data are a value and the probability of that value.
EmpiricalPar	This is the parameter that should be passed to the empirical distribution.
Erlang	This is the Erlang distribution.
ErlangPar	This is the parameter that should be passed to the Erlang distribution.
Exponential	This is the Exponential distribution (see the constructor description for its pdf definition).
ExponentialPar	This is the parameter that should be passed to the Exponential distribution.
GammaDistr	This is the Gamma distribution (see the constructor description for its pdf definition).
GammaDistrPar	This is the parameter that should be passed to the Gamma distribution.
HyperExp	This is the Hyperexponential distribution (see the constructor description for details).
HyperExpPar	This is the parameter that should be passed to the Hyperexponential distribution.
Lognormal	This is the Lognormal distribution (see the constructor description for its pdf definition).
LognormalPar	This is the parameter that should be passed to the Normal distribution.
MAPDistr	This is the MAP distribution.
MAPPar	This is the parameter that should be passed to the MAP distribution.
MMPP2Distr	This is the MMPP2 distribution.
MMPP2Par	This is the parameter that should be passed to the MMPP2 distribution.
Normal	This is the Normal distribution (see the constructor description for its pdf definition).
NormalPar	This is the parameter that should be passed to the Normal distribution.
Parameter	interface for all distributions parameters.
Pareto	This is the Pareto distribution (see the constructor description for its pdf definition).
ParetoPar	This is the parameter that should be passed to the Pareto distribution.
PhaseTypeDistr	This is the Phase-Type distribution.
PhaseTypePar	This is the parameter that should be passed to the Phase-Type distribution.
Poisson	This is the Poisson distribution.
PoissonPar	This is the parameter that should be passed to the Poisson distribution.
Replayer	Replays cyclically data, previously generated, reading them from a file.
ReplayerPar	Manages the file containing numbers (previously generated).
StorableDistribution	A marker interface for distributions to be stored in the DistributionContainer.
StudentT	This is the StudentT distribution (see the constructor description for its pdf definition).
StudentTPar	This is the parameter that should be passed to the StudentT distribution.
Uniform	This is the Uniform distribution.This object offers many methods to obtain random value distributed like a uniform.
UniformPar	This is the parameter that should be passed to the Uniform distribution.
Weibull	This is the Weibull distribution.
WeibullPar	This is the parameter that should be passed to the Weibull distribution.