Random Variable Distributions [Core]

Collaboration diagram for Random Variable Distributions:

Classes
class	ns3::RandomVariable
	The basic RNG for NS-3.Note: The underlying random number generation method used by NS-3 is the RngStream code by Pierre L'Ecuyer at the University of Montreal. More...
class	ns3::UniformVariable
	The uniform distribution RNG for NS-3.This class supports the creation of objects that return random numbers from a fixed uniform distribution. It also supports the generation of single random numbers from various uniform distributions. More...
class	ns3::ConstantVariable
	A random variable that returns a constantClass ConstantVariable defines a random number generator that returns the same value every sample. More...
class	ns3::SequentialVariable
	Return a sequential list of valuesClass SequentialVariable defines a random number generator that returns a sequential sequence. The sequence monotonically increases for a period, then wraps around to the low value and begins monotonicaly increasing again. More...
class	ns3::ExponentialVariable
	Exponentially Distributed random varThis class supports the creation of objects that return random numbers from a fixed exponential distribution. It also supports the generation of single random numbers from various exponential distributions. More...
class	ns3::ParetoVariable
	ParetoVariable distributed random varThis class supports the creation of objects that return random numbers from a fixed pareto distribution. It also supports the generation of single random numbers from various pareto distributions. More...
class	ns3::WeibullVariable
	WeibullVariable distributed random varThis class supports the creation of objects that return random numbers from a fixed weibull distribution. It also supports the generation of single random numbers from various weibull distributions. More...
class	ns3::NormalVariable
	Class NormalVariable defines a random variable with a normal (Gaussian) distribution.This class supports the creation of objects that return random numbers from a fixed normal distribution. It also supports the generation of single random numbers from various normal distributions. More...
class	ns3::EmpiricalVariable
	EmpiricalVariable distribution random varDefines a random variable that has a specified, empirical distribution. The distribution is specified by a series of calls to the CDF member function, specifying a value and the probability that the function value is less than the specified value. When values are requested, a uniform random variable is used to select a probabililty, and the return value is interpreted linerarly between the two appropriate points in the CDF. The method is known as inverse transform sampling: (http://en.wikipedia.org/wiki/Inverse_transform_sampling). More...
class	ns3::IntEmpiricalVariable
	Integer-based empirical distributionDefines an empirical distribution where all values are integers. Indentical to EmpiricalVariable, except that the inverse transform sampling interpolation described in the EmpiricalVariable documentation is modified to only return integers. More...
class	ns3::DeterministicVariable
	a non-random variableDefines a random variable that has a specified, predetermined sequence. This would be useful when trying to force the RNG to return a known sequence, perhaps to compare NS-3 to some other simulator More...
class	ns3::LogNormalVariable
	Log-normal Distributed random varLogNormalVariable defines a random variable with log-normal distribution. If one takes the natural logarithm of random variable following the log-normal distribution, the obtained values follow a normal distribution. This class supports the creation of objects that return random numbers from a fixed lognormal distribution. It also supports the generation of single random numbers from various lognormal distributions. More...
class	ns3::TriangularVariable
	Triangularly Distributed random varThis distribution is a triangular distribution. The probablility density is in the shape of a triangle. More...
class	ns3::RngStream
	Combined Multiple-Recursive Generator MRG32k3a. More...