public class GammaDistribution extends ContinuousDistribution
Meaning: | The gamma distribution may, e.g., be applied to characterize video traffic. Special cases contained are the negative-exponential and Erlang k distribution \((\alpha = 1 \mbox{ or } \alpha = k)\) |
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Parameters: |
|
PDF: | \(P(T=t) = f(t) = \frac{\beta^{-\alpha} \cdot t^{\alpha-1} \cdot
exp(-\frac{t}{\beta})}{ \Gamma(\alpha)} \mbox{ for } t>0\) whereby \(\Gamma(x)\) is the gamma function |
DF: | exists only if \(\alpha\) is an integer number and positive (see Erlang k distribution) |
Expected value: | \(E[T]= \alpha\beta\) |
Variance: | \(VAR[T]= \alpha\beta^2\) |
Coefficient of variation: | \(c_T= \frac{1}{\sqrt{\alpha}}\) |
Parser example: |
[...].Distribution = Gamma
or with the mean value and variation coefficient:
[...].Distribution.Mean = 4.5
|
References: | Law/Kelton fourth edition, pp. 284-286 |
Modifier and Type | Field and Description |
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double |
A |
double |
alpha |
double |
B |
double |
beta |
double |
D |
double |
Q |
double |
theta |
rng
CREATE_INSTANCE_METHOD_NAME
Constructor and Description |
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GammaDistribution(double alpha,
double beta) |
GammaDistribution(double alpha,
double beta,
RandomNumberGenerator rng) |
Modifier and Type | Method and Description |
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static GammaDistribution |
createInstance(SimNode ownNode,
Parameters pars,
RandomNumberGenerator rng)
as required by
ReflectionConstructable |
double |
next()
Create random numbers
|
getDefaultRNG, getRandomNumberGenerator, reset
public final double alpha
public final double beta
public final double A
public final double B
public final double D
public final double Q
public final double theta
public GammaDistribution(double alpha, double beta, RandomNumberGenerator rng)
public GammaDistribution(double alpha, double beta)
public static GammaDistribution createInstance(SimNode ownNode, Parameters pars, RandomNumberGenerator rng)
ReflectionConstructable
public double next()
ContinuousDistribution
next
in class ContinuousDistribution