Package jline.lang.processes

Class MarkedMMPP

java.lang.Object

jline.lang.processes.Distribution

jline.lang.processes.ContinuousDistribution

jline.lang.processes.Markovian

jline.lang.processes.MarkovModulated

jline.lang.processes.Marked

jline.lang.processes.MarkedMMPP

All Implemented Interfaces:

Serializable, Copyable

public class MarkedMMPP
extends Marked
implements Serializable

A Marked Markov-Modulated Poisson Process (M3PP)

See Also:

• Serialized Form

Field Summary

Fields inherited from class jline.lang.processes.Markovian

nPhases, process

Fields inherited from class jline.lang.processes.Distribution

immediate, mean, name, numParam, params, support

Constructor Summary

Constructors

Constructor	Description
MarkedMMPP()
MarkedMMPP(MatrixCell mmap)

Method Summary

Modifier and Type	Method	Description
double	evalCDF(double t)	Evaluates the cumulative distribution function (CDF) at time t.
double	evalLST(double s)	Evaluates the Laplace-Stieltjes Transform (LST) at parameter s.
MatrixCell	getProcess()	Returns the process representation as a MatrixCell.
double	getRate()	Gets the rate of this distribution (inverse of mean).
double	getSCV()	Gets the squared coefficient of variation (SCV) of this distribution.
double	getSkewness()	Gets the skewness of this distribution.
double	getVar()	Gets the variance of this distribution.
void	normalize()	Normalizes the MarkedMMPP so that D0+sum(D_i) rows form a proper infinitesimal generator.
double[]	sample(int n)	Generates random samples from this distribution using default random generator.
double[]	sample(int n, Random random)	Generates samples from the MarkedMMPP using the specified random generator.
MarkedMMPP	toTimeReversed()

Methods inherited from class jline.lang.processes.Marked

D, D, getD1k

Methods inherited from class jline.lang.processes.MarkovModulated

evalACFT, getACFDecay

Methods inherited from class jline.lang.processes.Markovian

acf, embedded, embeddedProb, evalCDF, evalMeanT, evalVarT, getACF, getEmbedded, getEmbeddedProb, getIDC, getIDI, getInitProb, getMean, getMoments, getMu, getNumberOfPhases, getPhi, getSubgenerator, getVariance, idc, idi, initProb, mean, moments, mu, numberOfPhases, numPhases, phi, process, rate, scv, setMean, setProcess, setRate, skewness, subgenerator, var, variance

Methods inherited from class jline.lang.processes.Distribution

evalProbInterval, getName, getNumParams, getParam, getSupport, isContinuous, isDisabled, isDiscrete, isImmediate, isMarkovian, name, numParams, param, setNumParams, setParam, support

Methods inherited from class java.lang.Object

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

Methods inherited from interface jline.lang.Copyable

copy

Constructor Details

MarkedMMPP

public MarkedMMPP()

MarkedMMPP

public MarkedMMPP(MatrixCell mmap)

Method Details

evalCDF

public double evalCDF(double t)

Evaluates the cumulative distribution function (CDF) at time t.

Overrides:

evalCDF in class Markovian

Parameters:

t - the time value

Returns:

the CDF value at time t

evalLST

public double evalLST(double s)

Evaluates the Laplace-Stieltjes Transform (LST) at parameter s.

Overrides:

evalLST in class Markovian

Parameters:

s - the transform parameter

Returns:

the LST value at parameter s

getProcess

public MatrixCell getProcess()

Returns the process representation as a MatrixCell.

Overrides:

getProcess in class Markovian

Returns:

the process matrices

getRate

public double getRate()

Description copied from class: Distribution

Gets the rate of this distribution (inverse of mean).

Overrides:

getRate in class Markovian

Returns:

the rate value (1/mean)

getSCV

public double getSCV()

Description copied from class: Distribution

Gets the squared coefficient of variation (SCV) of this distribution. SCV = Var(X) / E[X]^2.

Overrides:

getSCV in class Markovian

Returns:

the squared coefficient of variation

getSkewness

public double getSkewness()

Description copied from class: Distribution

Gets the skewness of this distribution. Skewness measures the asymmetry of the probability distribution.

Overrides:

getSkewness in class Markovian

Returns:

the skewness value

getVar

public double getVar()

Description copied from class: Distribution

Gets the variance of this distribution. Computed as SCV * mean^2.

Overrides:

getVar in class Markovian

Returns:

the variance

normalize

public void normalize()

Normalizes the MarkedMMPP so that D0+sum(D_i) rows form a proper infinitesimal generator. For MMPP, all D_i matrices should be diagonal with non-negative elements.

sample

public double[] sample(int n)

Description copied from class: Distribution

Generates random samples from this distribution using default random generator.

Overrides:

sample in class Markovian

Parameters:

n - the number of samples to generate

Returns:

array of random samples

sample

public double[] sample(int n,
 Random random)

Generates samples from the MarkedMMPP using the specified random generator.

Overrides:

sample in class Markovian

Parameters:

n - the number of samples to generate

random - the random number generator to use

Returns:

array of inter-arrival times

toTimeReversed

public MarkedMMPP toTimeReversed()