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ns3::LogNormalVariable Class Reference

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...

#include <random-variable.h>

+ Inheritance diagram for ns3::LogNormalVariable:

Public Member Functions

 LogNormalVariable (double mu, double sigma)
 
- Public Member Functions inherited from ns3::RandomVariable
 RandomVariable (const RandomVariable &o)
 
uint32_t GetInteger (void) const
 Returns a random integer integer from the underlying distribution. More...
 
double GetValue (void) const
 Returns a random double from the underlying distribution. More...
 
RandomVariableoperator= (const RandomVariable &o)
 

Additional Inherited Members

- Protected Member Functions inherited from ns3::RandomVariable
 RandomVariable (const RandomVariableBase &variable)
 
RandomVariableBasePeek (void) const
 

Detailed Description

Log-normal Distributed random var

LogNormalVariable 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.

The probability density function is defined over the interval [0,+inf) as: $ \frac{1}{x\sigma\sqrt{2\pi}} e^{-\frac{(ln(x) - \mu)^2}{2\sigma^2}}$ where $ mean = e^{\mu+\frac{\sigma^2}{2}} $ and $ variance = (e^{\sigma^2}-1)e^{2\mu+\sigma^2}$

The $ \mu $ and $ \sigma $ parameters can be calculated if instead the mean and variance are known with the following equations: $ \mu = ln(mean) - \frac{1}{2}ln\left(1+\frac{variance}{mean^2}\right)$, and, $ \sigma = \sqrt{ln\left(1+\frac{variance}{mean^2}\right)}$

Definition at line 544 of file random-variable.h.

Constructor & Destructor Documentation

ns3::LogNormalVariable::LogNormalVariable ( double  mu,
double  sigma 
)
Parameters
mumu parameter of the lognormal distribution
sigmasigma parameter of the lognormal distribution

Definition at line 1498 of file random-variable.cc.

References NS_LOG_FUNCTION.


The documentation for this class was generated from the following files: