Package jline.lang.processes

Class APH

java.lang.Object

jline.lang.processes.Distribution

jline.lang.processes.ContinuousDistribution

jline.lang.processes.Markovian

jline.lang.processes.APH

All Implemented Interfaces:

Serializable, Copyable

public class APH
extends Markovian

An acyclic phase type distribution

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
APH(List<Double> alpha, Matrix T)
APH(Matrix alpha, Matrix T)

Method Summary

Modifier and Type	Method	Description
Matrix	evalCDFMatrix()	Evaluates the CDF at default time points and returns as a Matrix.
Matrix	evalCDFMatrix(double[] timePoints)	Evaluates the CDF at specified time points and returns as a Matrix.
double	evalLST(double s)	Evaluate the Laplace-Stieltjes Transform at s
static APH	fit(double mean, double scv, double skew)
static APH	fitCentral(double mean, double var, double skew)
static APH	fitMeanAndSCV(double mean, double scv)
static APH	fitRawMoments(double m1, double m2, double m3)	Fits an APH distribution from the first three raw moments.
Matrix	getInitProb()	Gets the initial probability vector.
Matrix	getSubgenerator()
Matrix	initProb()	Kotlin-style property alias for getInitProb()

Methods inherited from class jline.lang.processes.Markovian

acf, D, embedded, embeddedProb, evalCDF, evalCDF, evalMeanT, evalVarT, getACF, getEmbedded, getEmbeddedProb, getIDC, getIDI, getMean, getMoments, getMu, getNumberOfPhases, getPhi, getProcess, getRate, getSCV, getSkewness, getVar, getVariance, idc, idi, mean, moments, mu, numberOfPhases, numPhases, phi, process, rate, sample, sample, 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

APH

public APH(List<Double> alpha,
 Matrix T)

APH

public APH(Matrix alpha,
 Matrix T)

Method Details

getSubgenerator

public Matrix getSubgenerator()

Overrides:

getSubgenerator in class Markovian

fit

public static APH fit(double mean,
 double scv,
 double skew)

fitCentral

public static APH fitCentral(double mean,
 double var,
 double skew)

fitMeanAndSCV

public static APH fitMeanAndSCV(double mean,
 double scv)

fitRawMoments

public static APH fitRawMoments(double m1,
 double m2,
 double m3)

Fits an APH distribution from the first three raw moments.

Parameters:

m1 - First raw moment (mean)

m2 - Second raw moment

m3 - Third raw moment

Returns:

APH distribution fitted to the given moments

evalLST

public double evalLST(double s)

Description copied from class: Distribution

Evaluate the Laplace-Stieltjes Transform at s

Overrides:

evalLST in class Markovian

Parameters:

s - the Laplace domain variable

Returns:

the LST value at s

getInitProb

public Matrix getInitProb()

Description copied from class: Markovian

Gets the initial probability vector.

Overrides:

getInitProb in class Markovian

Returns:

the initial probabilities

initProb

public Matrix initProb()

Kotlin-style property alias for getInitProb()

Overrides:

initProb in class Markovian

evalCDFMatrix

public Matrix evalCDFMatrix()

Evaluates the CDF at default time points and returns as a Matrix. Returns a matrix with [CDF_value, time] pairs (matching MATLAB format).

Returns:

Matrix with numPoints rows and 2 columns [CDF, time]

evalCDFMatrix

public Matrix evalCDFMatrix(double[] timePoints)

Evaluates the CDF at specified time points and returns as a Matrix.

Parameters:

timePoints - Array of time points at which to evaluate the CDF

Returns:

Matrix with timePoints.length rows and 2 columns [CDF, time]