Uses of Interface
random.Parameter

Packages that use Parameter

Package	Description
NetStrategies.ImpatienceStrategies	Impatience strategies that model customers leaving a queue before being served, either by balking (refusing to join the queue) or reneging (abandoning the queue after joining).
NetStrategies.ServiceStrategies	Service time strategies determining the service time of jobs at a station, including load independent and load dependent service distributions.
NetStrategies.VacationStrategies	Vacation strategies modelling servers that suspend their service for a vacation period, as supported by the extended JSIM simulation engine.
QueueNet	Queueing network model of the JSIM simulation engine: nodes, stations, jobs, job classes, measures and the global structures that connect them.
random	Random number generation for the JSIM simulation engine.
random.discrete	Discrete probability distributions for the JSIM simulation engine (Bernoulli, binomial, geometric, Poisson, uniform, ...).

Uses of Parameter in NetStrategies.ImpatienceStrategies

Constructors in NetStrategies.ImpatienceStrategies with parameters of type Parameter

Modifier	Constructor	Description
	Reneging(Distribution distribution, Parameter parameter)

Uses of Parameter in NetStrategies.ServiceStrategies

Fields in NetStrategies.ServiceStrategies declared as Parameter

Modifier and Type	Field	Description
protected Parameter	ServiceTimeStrategy.parameter	Distribution parameters.

Methods in NetStrategies.ServiceStrategies that return Parameter

Modifier and Type	Method	Description
Parameter	LDParameter.getDistrParameter()	Gets the parameter of the distribution used to evaluate service time
Parameter	ServiceTimeStrategy.getParameter()

Methods in NetStrategies.ServiceStrategies with parameters of type Parameter

Modifier and Type	Method	Description
boolean	ServiceTimeStrategy.setParameter(Parameter parameter)	Sets the parameters of the distribution.

Constructors in NetStrategies.ServiceStrategies with parameters of type Parameter

Modifier	Constructor	Description
	LDParameter(Integer from, Distribution distr, Parameter parameter)	Construct a new Load Dependent Service Strategy parameter
	LDParameter(Integer from, Distribution distr, Parameter parameter, String function)	Construct a new Load Dependent Service Strategy parameter
	ServiceTimeStrategy(Distribution distribution, Parameter parameter)	Creates a new instance of ServiceTime.

Uses of Parameter in NetStrategies.VacationStrategies

Constructors in NetStrategies.VacationStrategies with parameters of type Parameter

Modifier	Constructor	Description
	BernoulliVacationStrategy(Double p, Distribution vacationTimeDistr, Parameter vacationTimePar)
	VacationWhenIdleStrategy(Integer type, Distribution vacationTimeDistr, Parameter vacationTimePar)

Uses of Parameter in QueueNet

Methods in QueueNet that return Parameter

Modifier and Type	Method	Description
Parameter	NodeSection.getParameter(int id)	Gets a parameter type property of this node.
Parameter	NodeSection.getParameter(int id, JobClass jobClass)	Gets a parameter type property of this node depending on a specified job class.

Uses of Parameter in random

Classes in random that implement Parameter

Modifier and Type	Class	Description
class	BatchPar	This is the parameter that should be passed to the Batched distribution.
class	BurstPar	This is the parameter that should be passed to the Burst distribution.
class	CoxianPar	This is the parameter that should be passed to the Coxian distribution.
class	DeterministicDistrPar	This is the parameter that should be passed to the Deterministic distribution.
class	EmpiricalPar	This is the parameter that should be passed to the empirical distribution.
class	ErlangPar	This is the parameter that should be passed to the Erlang distribution.
class	ExponentialPar	This is the parameter that should be passed to the Exponential distribution.
class	GammaDistrPar	This is the parameter that should be passed to the Gamma distribution.
class	HyperExpPar	This is the parameter that should be passed to the Hyperexponential distribution.
class	LognormalPar	This is the parameter that should be passed to the Normal distribution.
class	MAPPar	This is the parameter that should be passed to the MAP distribution.
class	MMPP2Par	This is the parameter that should be passed to the MMPP2 distribution.
class	NormalPar	This is the parameter that should be passed to the Normal distribution.
class	ParetoPar	This is the parameter that should be passed to the Pareto distribution.
class	PhaseTypePar	This is the parameter that should be passed to the Phase-Type distribution.
class	PoissonPar	This is the parameter that should be passed to the Poisson distribution.
class	ReplayerPar	Manages the file containing numbers (previously generated).
class	StudentTPar	This is the parameter that should be passed to the StudentT distribution.
class	UniformPar	This is the parameter that should be passed to the Uniform distribution.
class	WeibullPar	This is the parameter that should be passed to the Weibull distribution.

Fields in random declared as Parameter

Modifier and Type	Field	Description
protected Parameter	DistributionContainer.parameter

Methods in random that return Parameter

Modifier and Type	Method	Description
Parameter	BatchPar.getBaseParameter()
Parameter	BatchPar.getBatchSizeParameter()
Parameter	DistributionContainer.getParameter()	Get method for the distribution parameter
Parameter	BurstPar.getValueParameterA()	Returns the parameter of value distribution A.
Parameter	BurstPar.getValueParameterB()	Returns the parameter of value distribution B.

Methods in random with parameters of type Parameter

Modifier and Type	Method	Description
double	Batch.cdf(double x, Parameter p)
double	Burst.cdf(double x, Parameter p)
double	CoxianDistr.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	DeterministicDistr.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Distribution.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Empirical.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Erlang.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Exponential.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	GammaDistr.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	HyperExp.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Lognormal.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	MAPDistr.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	MMPP2Distr.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Normal.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Pareto.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	PhaseTypeDistr.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Poisson.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Replayer.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	StudentT.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Uniform.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
double	Weibull.cdf(double x, Parameter p)	This method is used to obtain from the distribution its cumulative distribution function evaluated where required by the user.
int	Uniform.nextInt(Parameter p)	This method is used to obtain from the distribution the next integer number distributed according to the distribution parameter.
double	Uniform.nextLong(Parameter p)	This method is used to obtain from the distribution the next Long integer number distributed according to the distribution parameter.
double	Batch.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Burst.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter and the actual interval (A or B).
double	CoxianDistr.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	DeterministicDistr.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Distribution.nextRand(Parameter p)	This method is used to ask all the distribution to return a new random number distributed according to the distribution name.
double	Empirical.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Erlang.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Exponential.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	GammaDistr.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	HyperExp.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Lognormal.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	MAPDistr.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	MMPP2Distr.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Normal.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Pareto.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	PhaseTypeDistr.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Poisson.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Replayer.nextRand(Parameter p)	Reads a new data from the file.
double	StudentT.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Uniform.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Weibull.nextRand(Parameter p)	This method is used to obtain from the distribution the next number distributed according to the distribution parameter.
double	Batch.pdf(double x, Parameter p)
double	Burst.pdf(double x, Parameter p)
double	CoxianDistr.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	DeterministicDistr.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Distribution.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Empirical.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Erlang.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Exponential.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	GammaDistr.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	HyperExp.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Lognormal.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	MAPDistr.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	MMPP2Distr.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Normal.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Pareto.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	PhaseTypeDistr.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Poisson.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Replayer.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	StudentT.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Uniform.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
double	Weibull.pdf(double x, Parameter p)	This method is used to obtain from the distribution its probability distribution function evaluated where required by the user.
void	BatchPar.setBaseParameter(Parameter baseParameter)
void	BatchPar.setBatchSizeParameter(Parameter batchSizeParameter)
void	BurstPar.setValueParameterA(Parameter parameterA)	Sets the the parameter of value distribution A.
void	BurstPar.setValueParameterB(Parameter parameterB)	Sets the the parameter of value distribution B.
double	Batch.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Burst.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	CoxianDistr.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	DeterministicDistr.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Distribution.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Empirical.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean, which is is calculated from the data provided by the user (contained in the parameter p) as the sum of all the data value, divided by the number of data.
double	Erlang.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Exponential.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	GammaDistr.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	HyperExp.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Lognormal.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	MAPDistr.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	MMPP2Distr.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Normal.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Pareto.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	PhaseTypeDistr.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Poisson.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Replayer.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	StudentT.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Uniform.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Weibull.theorMean(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic mean.
double	Batch.theorVariance(Parameter p)
double	Burst.theorVariance(Parameter p)
double	CoxianDistr.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	DeterministicDistr.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Distribution.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Empirical.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance which is calculated from the data provided by the user (contained in the parameter p) as the sum of all the squares of the differences between each data value and the theoretic mean, divided by the number of data.
double	Erlang.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Exponential.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	GammaDistr.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	HyperExp.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Lognormal.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	MAPDistr.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	MMPP2Distr.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Normal.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Pareto.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	PhaseTypeDistr.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Poisson.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Replayer.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	StudentT.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Uniform.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.
double	Weibull.theorVariance(Parameter p)	This method is used to obtain from the distribution the value of its own theoretic variance.

Constructors in random with parameters of type Parameter

Modifier	Constructor	Description
	DistributionContainer(StorableDistribution distribution, Parameter parameter)	Constructs a Distribution Container with a given distribution and a parameter

Uses of Parameter in random.discrete

Classes in random.discrete that implement Parameter

Modifier and Type	Class	Description
class	BernoulliPar	Parameters of the Bernoulli distribution.
class	BinomialPar	Parameters of the binomial distribution.
class	PoissonPar	Parameters of the Poisson distribution.
class	ShiftedGeometricPar	Parameters of the shifted geometric distribution.
class	UniformPar	Parameters of the discrete uniform distribution.
class	ZipfPar	Parameters of the Zipf distribution.

Methods in random.discrete with parameters of type Parameter

Modifier and Type	Method	Description
double	Bernoulli.cdf(int x, Parameter p)
double	Binomial.cdf(int x, Parameter par)
abstract double	DiscreteDistribution.cdf(int x, Parameter p)	obtain the cumulative distribution from the distribution
double	FixProbability.cdf(int x, Parameter p)
double	Poisson.cdf(int x, Parameter p)
double	ShiftedGeometric.cdf(int x, Parameter p)
double	Uniform.cdf(int x, Parameter p)
double	Zipf.cdf(int x, Parameter p)
protected Hashtable<Integer,Double>	DiscreteDistribution.createdCDFList(int lower, int upper, Parameter p)
int	Bernoulli.nextRand(Parameter p)
int	Binomial.nextRand(Parameter par)
abstract int	DiscreteDistribution.nextRand(Parameter p)	Generate random variables that follow an probability distribution
int	FixProbability.nextRand(Parameter p)
int	Poisson.nextRand(Parameter p)
int	ShiftedGeometric.nextRand(Parameter p)
int	Uniform.nextRand(Parameter p)
int	Zipf.nextRand(Parameter p)
double	Bernoulli.pmf(int x, Parameter p)
double	Binomial.pmf(int x, Parameter par)
abstract double	DiscreteDistribution.pmf(int x, Parameter p)	obtain the probability distribution from the distribution
double	FixProbability.pmf(int x, Parameter p)
double	Poisson.pmf(int x, Parameter p)
double	ShiftedGeometric.pmf(int x, Parameter p)
double	Uniform.pmf(int x, Parameter p)
double	Zipf.pmf(int x, Parameter p)
double	Bernoulli.theorMean(Parameter p)
double	Binomial.theorMean(Parameter par)
abstract double	DiscreteDistribution.theorMean(Parameter p)	Calculate the Mean value from the parameter of the distribution
double	FixProbability.theorMean(Parameter p)
double	Poisson.theorMean(Parameter p)
double	ShiftedGeometric.theorMean(Parameter p)
double	Uniform.theorMean(Parameter p)
double	Zipf.theorMean(Parameter p)
double	Bernoulli.theorVariance(Parameter p)
double	Binomial.theorVariance(Parameter par)
abstract double	DiscreteDistribution.theorVariance(Parameter p)	Calculate the Variance from the parameter of the distribution
double	FixProbability.theorVariance(Parameter p)
double	Poisson.theorVariance(Parameter p)
double	ShiftedGeometric.theorVariance(Parameter p)
double	Uniform.theorVariance(Parameter p)
double	Zipf.theorVariance(Parameter p)
protected <T> T	Poisson.unboxParameter(Parameter p, Function<Double,T> function)
protected <T> T	ShiftedGeometric.unboxParameter(Parameter p, Function<Double,T> function)
boolean	Bernoulli.updatePar(Parameter p)
boolean	Binomial.updatePar(Parameter p)
abstract boolean	DiscreteDistribution.updatePar(Parameter p)	Sub-class must implement this method to update parameter.
boolean	FixProbability.updatePar(Parameter p)
boolean	Poisson.updatePar(Parameter p)
boolean	ShiftedGeometric.updatePar(Parameter p)
boolean	Uniform.updatePar(Parameter p)
boolean	Zipf.updatePar(Parameter p)