Package jline.lang.processes

Class MarkovChain

java.lang.Object

jline.lang.processes.Process

jline.lang.processes.MarkovChain

All Implemented Interfaces:

Serializable

public class MarkovChain
extends Process

A class for a discrete time Markov chain

See Also:

• Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected boolean	isfinite
protected Matrix	stateSpace
protected Matrix	transMat

Fields inherited from class jline.lang.processes.Process

name, params

Constructor Summary

Constructors

Constructor	Description
MarkovChain(Matrix transMat)	Creates a DTMC with the specified transition matrix
MarkovChain(Matrix transMat, boolean isFinite)	Creates a DTMC with the specified transition matrix and finite flag

Method Summary

Modifier and Type	Method	Description
static MarkovChain	fromSampleSysAggr(Object sa)	Create DTMC from sample system aggregation (legacy interface)
static MarkovChain	fromSampleSysAggr(Matrix samples)	Create DTMC from sample system aggregation
static MarkovChain	fromSampleSysAggr(Matrix samples, int numStates)	Create DTMC from sample system aggregation
Matrix	getStateSpace()	Get the state space
Matrix	getTransMat()	Get the transition matrix
boolean	isFinite()	Check if the DTMC is finite
static MarkovChain	rand(int nStates)	Create a random DTMC
Matrix	sample()	Sample from the DTMC
Matrix	sample(int n)	Sample n steps from the DTMC starting from initial distribution
Matrix	sample(int n, Matrix pi0, Random random)	Sample n steps from the DTMC
void	setStateSpace(Matrix stateSpace)	Set the state space
MarkovProcess	toCTMC()	Convert to CTMC by subtracting identity matrix
MarkovChain	toTimeReversed()	Get time-reversed DTMC

Methods inherited from class jline.lang.processes.Process

getName, getNumParams, getParam, name, numParams, param, setParam

Methods inherited from class java.lang.Object

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

Field Details

transMat

protected Matrix transMat

stateSpace

protected Matrix stateSpace

isfinite

protected boolean isfinite

Constructor Details

MarkovChain

public MarkovChain(Matrix transMat)

Creates a DTMC with the specified transition matrix

Parameters:

transMat - the transition matrix

MarkovChain

public MarkovChain(Matrix transMat,
 boolean isFinite)

Creates a DTMC with the specified transition matrix and finite flag

Parameters:

transMat - the transition matrix

isFinite - whether the DTMC is finite

Method Details

toCTMC

public MarkovProcess toCTMC()

Convert to CTMC by subtracting identity matrix

Returns:

the equivalent CTMC

toTimeReversed

public MarkovChain toTimeReversed()

Get time-reversed DTMC

Returns:

time-reversed DTMC

getTransMat

public Matrix getTransMat()

Get the transition matrix

Returns:

the transition matrix

setStateSpace

public void setStateSpace(Matrix stateSpace)

Set the state space

Parameters:

stateSpace - the state space matrix

getStateSpace

public Matrix getStateSpace()

Get the state space

Returns:

the state space matrix

isFinite

public boolean isFinite()

Check if the DTMC is finite

Returns:

true if finite

sample

public Matrix sample()

Sample from the DTMC

Specified by:

sample in class Process

Returns:

sampled value

sample

public Matrix sample(int n)

Sample n steps from the DTMC starting from initial distribution

Parameters:

n - number of steps to sample

Returns:

matrix containing sampled states (column vector)

sample

public Matrix sample(int n,
 Matrix pi0,
 Random random)

Sample n steps from the DTMC

Parameters:

n - number of steps to sample

pi0 - initial state distribution (if null, uses uniform distribution)

random - random number generator

Returns:

matrix containing sampled states (column vector)

rand

public static MarkovChain rand(int nStates)

Create a random DTMC

Parameters:

nStates - number of states

Returns:

random DTMC

fromSampleSysAggr

public static MarkovChain fromSampleSysAggr(Matrix samples)

Create DTMC from sample system aggregation

Parameters:

samples - matrix where each row is a sample trajectory, each column is a time step

Returns:

DTMC constructed from samples by estimating transition probabilities

fromSampleSysAggr

public static MarkovChain fromSampleSysAggr(Matrix samples,
 int numStates)

Create DTMC from sample system aggregation

Parameters:

samples - matrix where each row is a sample trajectory, each column is a time step

numStates - number of states (if -1, infer from data)

Returns:

DTMC constructed from samples by estimating transition probabilities

fromSampleSysAggr

public static MarkovChain fromSampleSysAggr(Object sa)

Create DTMC from sample system aggregation (legacy interface)

Parameters:

sa - the sample aggregation object

Returns:

DTMC constructed from samples