public class BernoulliDistribution extends DiscreteDistribution
| Meaning: | Single random experiment with the success probability \(q (0 \le q \le 1)\) |
|---|---|
| Parameters: | Success probability = mean value \(q\) |
| Distribution: | \(P(X=i) = p_i = \begin{cases} 1-q &\mbox{for } i=0 \\ q &\mbox{for } i=1 \\ 0 & \mbox{else } \end{cases} \) |
| Expected value: | \(E[X]=q\) |
| Variance: | \(VAR[X]=q(1-q)\) |
| Coefficient of variation: | \(c_T=\sqrt{ \frac{ 1-q }{q} }\) |
| Generating func.: | \(G(z)=1-q+qz \) |
| Parser example: |
[...].Distribution = Bernoulli
|
| Modifier and Type | Field and Description |
|---|---|
double |
mean |
rngCREATE_INSTANCE_METHOD_NAME| Constructor and Description |
|---|
BernoulliDistribution(double mean) |
BernoulliDistribution(double mean,
RandomNumberGenerator rng) |
| Modifier and Type | Method and Description |
|---|---|
static BernoulliDistribution |
createInstance(SimNode ownNode,
Parameters pars,
RandomNumberGenerator rng)
as required by
ReflectionConstructable |
int |
next()
Create random numbers
|
getDefaultRNG, getRandomNumberGenerator, resetpublic BernoulliDistribution(double mean,
RandomNumberGenerator rng)
public BernoulliDistribution(double mean)
public static BernoulliDistribution createInstance(SimNode ownNode, Parameters pars, RandomNumberGenerator rng)
ReflectionConstructablepublic int next()
DiscreteDistributionnext in class DiscreteDistribution