public class ConstantDistribution extends ContinuousDistribution
| Meaning: | A constant value \(d\) is returned |
|---|---|
| Parameters: | constant ("mean") value \(d\) |
| PDF: | \(P(T=t) = f(t) = \delta(t-d) \) |
| DF: | \(P(T \le t) = F(t) = \sigma(t-d) = \begin{cases} 0 &\mbox{for } t < d \\ 1 & \mbox{else } \end{cases} \) |
| Expected value: | \(E[T]= d \) |
| Variance: | \(VAR[T]= 0\) |
| Coefficient of variation: | \(c_T= 0\) |
| LST: | \(\phi(s) = exp(-sd)\) |
| Parser example: |
[...].Distribution = ikr.simlib.distributions.continuous.ConstantDistribution
|
| Modifier and Type | Field and Description |
|---|---|
double |
mean |
rngCREATE_INSTANCE_METHOD_NAME| Constructor and Description |
|---|
ConstantDistribution(double mean) |
ConstantDistribution(SimNode ownNode,
Parameters pars) |
| Modifier and Type | Method and Description |
|---|---|
static ConstantDistribution |
createInstance(SimNode ownNode,
Parameters pars,
RandomNumberGenerator rng)
as required by
ReflectionConstructable |
double |
next()
Create random numbers
|
getDefaultRNG, getRandomNumberGenerator, resetpublic ConstantDistribution(double mean)
public ConstantDistribution(SimNode ownNode, Parameters pars)
public static ConstantDistribution createInstance(SimNode ownNode, Parameters pars, RandomNumberGenerator rng)
ReflectionConstructablepublic double next()
ContinuousDistributionnext in class ContinuousDistribution