ikr.simlib.distributions.continuous

Class HyperExpDistribution

java.lang.Object

ikr.simlib.distributions.Distribution

ikr.simlib.distributions.continuous.ContinuousDistribution

ikr.simlib.distributions.continuous.HyperExpDistribution

All Implemented Interfaces:

ReflectionConstructable, ReflectionConstructable3<SimNode,Parameters,RandomNumberGenerator>

public class HyperExpDistribution
extends ContinuousDistribution

Hyperexponential Distribution to the Order of k

Hyperexponential distribution to the order of k

Meaning:	Selecting one of \(k\) random variables that are negative-exponentially distributed with the individual parameters \(\lambda_i\) and the probabilities \(p_i\) (parallel switching in the phase model).
Parameters:	order \(k > 0\) rates \(\lambda_i\) or mean values \(m_i\) of the individual phases \((i = 1, \dots, k)\) branching probabilities \(p_i(i=1,...,k)\)
PDF:	\(P(T=t) = f(t) = \sum\limits_{i=1}^k \lambda_i \cdot p_i \cdot exp(-\lambda_i t) \)
DF:	\(P(T \le t) = F(t) = 1 - \sum\limits_{i=1}^k p_i \cdot exp(-\lambda_i t) \)
Expected value:	\(E[T]= \sum\limits_{i=1}^k \frac{p_i}{\lambda_i} \)
Variance:	\(VAR[T]= 2 \cdot \sum\limits_{i=1}^k \frac{p_i}{\lambda_i^2} - ( \sum\limits_{i=1}^k \frac{p_i}{\lambda_i} )^2 \)
Coefficient of variation:	\(c_T= \sqrt{\frac{2 \cdot \sum\limits_{i=1}^k \frac{p_i}{\lambda_i^2}}{(\sum\limits_{i=1}^k \frac{p_i}{\lambda_i})^2}} -1 \le 1\)
LST:	\(\phi(s) = \sum\limits_{i=1}^{k} p_i \cdot \frac{\lambda_i}{\lambda_i +s}\)
Parser example:	[...].Distribution = HypoExp [...].Distribution.Order = 2 [...].Distribution.Means = [ 2.5 , 8] [...].Distribution.BranchProbabilities = [ 0.4 0.6 ]

Field Summary

Fields

Modifier and Type	Field and Description
ProbabilityVector	branchProbs
NegExpDistribution[]	phases

Fields inherited from class ikr.simlib.distributions.Distribution

rng

Fields inherited from interface ikr.simlib.parameters.reflection.ReflectionConstructable

CREATE_INSTANCE_METHOD_NAME

Constructor Summary

Constructors

Constructor and Description
HyperExpDistribution(double[] means, double[] branchProbs)
HyperExpDistribution(double[] means, double[] branchProbs, RandomNumberGenerator rng)
HyperExpDistribution(double mean1, double mean2, double branchProb1)
HyperExpDistribution(double mean1, double mean2, double branchProb1, RandomNumberGenerator rng)

Method Summary

Methods

Modifier and Type	Method and Description
static HyperExpDistribution	createInstance(SimNode ownNode, Parameters pars, RandomNumberGenerator rng) as required by ReflectionConstructable
double	next() Create random numbers

Methods inherited from class ikr.simlib.distributions.Distribution

getDefaultRNG, getRandomNumberGenerator, reset

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

phases

public final NegExpDistribution[] phases

branchProbs

public final ProbabilityVector branchProbs

Constructor Detail

HyperExpDistribution

public HyperExpDistribution(double[] means,
                    double[] branchProbs,
                    RandomNumberGenerator rng)

HyperExpDistribution

public HyperExpDistribution(double[] means,
                    double[] branchProbs)

HyperExpDistribution

public HyperExpDistribution(double mean1,
                    double mean2,
                    double branchProb1,
                    RandomNumberGenerator rng)

HyperExpDistribution

public HyperExpDistribution(double mean1,
                    double mean2,
                    double branchProb1)

Method Detail

createInstance

public static HyperExpDistribution createInstance(SimNode ownNode,
                                  Parameters pars,
                                  RandomNumberGenerator rng)

as required by ReflectionConstructable

next

public double next()

Description copied from class: ContinuousDistribution

Create random numbers

Specified by:

next in class ContinuousDistribution