Package jline.lang.processes

Class DMAP

java.lang.Object

jline.lang.processes.Distribution

jline.lang.processes.ContinuousDistribution

jline.lang.processes.Markovian

jline.lang.processes.MarkovModulated

jline.lang.processes.DMAP

All Implemented Interfaces:

Serializable, Copyable

public class DMAP
extends MarkovModulated
implements Serializable

A Discrete Markovian Arrival Process (DMAP). Unlike MAP (continuous-time), D0+D1 is a stochastic matrix (row sums = 1).

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
DMAP()
DMAP(MatrixCell map)
DMAP(Matrix D0, Matrix D1)

Method Summary

Modifier and Type	Method	Description
Matrix	D(int i)	Gets the i-th matrix of the Markovian arrival process representation.
boolean	equals(Object obj)
double	evalCDF(double t)	CDF(t) = 1 - pi * D0^floor(t) * e
double	getMean()	Mean inter-arrival time: pi * (I - D0)^{-1} * e
Matrix	getMu()	Row sums of (I - D0).
long	getNumberOfPhases()	Gets the number of phases in this Markovian distribution.
MatrixCell	getProcess()	Gets the matrix representation of this Markovian process.
double	getRate()	Gets the rate of this distribution (inverse of mean).
double	getSCV()	Gets the squared coefficient of variation (SCV) of this distribution.
Matrix	getTransitionMatrix()	Embedded chain P = (I - D0)^{-1} * D1.
double	getVar()	Variance: 2*pi*(I-D0)^{-2}*e - mean - mean^2
int	hashCode()
void	normalize()
static DMAP	rand()
static DMAP	rand(int order)
double[]	sample(int n)	Generates random samples from this distribution using default random generator.
double[]	sample(int n, Random random)	Generates random samples from this distribution using the specified random generator.
String	toString()

Methods inherited from class jline.lang.processes.MarkovModulated

evalACFT, getACFDecay

Methods inherited from class jline.lang.processes.Markovian

acf, embedded, embeddedProb, evalCDF, evalLST, evalMeanT, evalVarT, getACF, getEmbedded, getEmbeddedProb, getIDC, getIDI, getInitProb, getMoments, getPhi, getSkewness, 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, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface jline.lang.Copyable

copy

Constructor Details

DMAP

public DMAP(MatrixCell map)

DMAP

public DMAP()

DMAP

public DMAP(Matrix D0,
 Matrix D1)

Method Details

rand

public static DMAP rand()

rand

public static DMAP rand(int order)

D

public Matrix D(int i)

Description copied from class: Markovian

Gets the i-th matrix of the Markovian arrival process representation.

Overrides:

D in class Markovian

Parameters:

i - the matrix index (0 for D0, 1 for D1, etc.)

Returns:

the matrix at index i

getMean

public double getMean()

Mean inter-arrival time: pi * (I - D0)^{-1} * e

Overrides:

getMean in class Markovian

Returns:

the mean value, or NaN if the process contains NaN values

getVar

public double getVar()

Variance: 2*pi*(I-D0)^{-2}*e - mean - mean^2

Overrides:

getVar in class Markovian

Returns:

the variance

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

getMu

public Matrix getMu()

Row sums of (I - D0).

Overrides:

getMu in class Markovian

Returns:

column vector of rates

sample

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

Description copied from class: Distribution

Generates random samples from this distribution 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 random samples

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

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)

evalCDF

public double evalCDF(double t)

CDF(t) = 1 - pi * D0^floor(t) * e

Overrides:

evalCDF in class Markovian

Parameters:

t - the point at which to evaluate the CDF

Returns:

the CDF value at point t

getTransitionMatrix

public Matrix getTransitionMatrix()

Embedded chain P = (I - D0)^{-1} * D1.

getNumberOfPhases

public long getNumberOfPhases()

Description copied from class: Markovian

Gets the number of phases in this Markovian distribution.

Overrides:

getNumberOfPhases in class Markovian

Returns:

the number of phases

normalize

public void normalize()

getProcess

public MatrixCell getProcess()

Description copied from class: Markovian

Gets the matrix representation of this Markovian process.

Overrides:

getProcess in class Markovian

Returns:

MatrixCell containing D0, D1, ... matrices

toString

public String toString()

Overrides:

toString in class Object

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object