Constructor Detail

• MarkovProcess

  MarkovProcess(Matrix infGen)

  Creates a CTMC with the specified infinitesimal generator

  Parameters:

  infGen - the infinitesimal generator matrix

• MarkovProcess

  MarkovProcess(Matrix infGen, boolean isFinite)

  Creates a CTMC with the specified infinitesimal generator and finite flag

  Parameters:

  infGen - the infinitesimal generator matrix

  isFinite - whether the CTMC is finite

• MarkovProcess

  MarkovProcess(Matrix infGen, boolean isFinite, Matrix stateSpace)

  Creates a CTMC with the specified infinitesimal generator, finite flag, and state space

  Parameters:

  infGen - the infinitesimal generator matrix

  isFinite - whether the CTMC is finite

  stateSpace - the state space representation

Method Detail

• toDTMC

   MarkovChain toDTMC()

  Convert to DTMC using uniformization

  Returns:

  the equivalent DTMC

• toDTMC

   MarkovChain toDTMC(double q)

• toTimeReversed

   MarkovProcess toTimeReversed()

  Get time-reversed CTMC

  Returns:

  time-reversed CTMC

• setStateSpace

   void setStateSpace(Matrix stateSpace)

  Set the state space

  Parameters:

  stateSpace - the state space matrix

• getGenerator

   Matrix getGenerator()

  Get the infinitesimal generator matrix

  Returns:

  the generator matrix

• getProbState

   double getProbState(int state)

  Get probability of a specific state using steady-state analysis

  Parameters:

  state - the state index (0-based)

  Returns:

  the probability of the specified state

• getProbState

   Matrix getProbState(Matrix state)

  Get probability of a specific state using Cramer's rule

  Parameters:

  state - the state vector (if state space is defined) or single state index

  Returns:

  the probability matrix containing the state probability

• solve

   Matrix solve()

  Solve the CTMC for steady-state probabilities

  Returns:

  the steady-state probability vector

• sample

   Matrix sample()

  Sample from the CTMC

  Returns:

  sampled value

• sample

   Matrix sample(int n)

  Sample n state transitions from the CTMC starting from steady-state

  Parameters:

  n - number of state transitions to sample

  Returns:

  matrix containing sampled states (column vector)

• sample

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

  Sample n state transitions from the CTMC

  Parameters:

  n - number of state transitions to sample

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

  random - random number generator

  Returns:

  matrix containing sampled states (column vector)

• getStateSpace

   Matrix getStateSpace()

  Get the state space

  Returns:

  the state space matrix

• isFinite

   boolean isFinite()

  Check if the CTMC is finite

  Returns:

  true if finite

• rand

   static MarkovProcess rand(int nStates)

  Create a random CTMC

  Parameters:

  nStates - number of states

  Returns:

  random CTMC

• fromSampleSysAggr

   static MarkovProcess fromSampleSysAggr(Matrix samples, Matrix sojournTimes)

  Create CTMC from sample system aggregation

  Parameters:

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

  sojournTimes - matrix of sojourn times corresponding to each state in samples

  Returns:

  CTMC constructed from samples by estimating transition rates

• fromSampleSysAggr

   static MarkovProcess fromSampleSysAggr(Matrix samples, Matrix sojournTimes, int numStates)

  Create CTMC from sample system aggregation

  Parameters:

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

  sojournTimes - matrix of sojourn times corresponding to each state in samples

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

  Returns:

  CTMC constructed from samples by estimating transition rates

• fromSampleSysAggr

   static MarkovProcess fromSampleSysAggr(Matrix samples)

  Create CTMC from sample system aggregation (assuming unit sojourn times)

  Parameters:

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

  Returns:

  CTMC constructed from samples with unit time steps

• fromSampleSysAggr

   static MarkovProcess fromSampleSysAggr(Object sa)

  Create CTMC from sample system aggregation (legacy interface)

  Parameters:

  sa - the sample aggregation object

  Returns:

  CTMC constructed from samples