|
This method returns the stationary vector in matricial form of a markovchain object.
● Data Source:
CranContrib
● Keywords:
● Alias: steadyStates
●
0 images
|
|
This function compute the first passage probability in states
● Data Source:
CranContrib
● Keywords:
● Alias: firstPassage
●
0 images
|
|
This method returns the states of a transition matrix.
● Data Source:
CranContrib
● Keywords:
● Alias: states
●
0 images
|
is.accessible
(Package: markovchain) :
Verify if a state j is reachable from state i.
This function verifies if a state is reachable from another, i.e., if exists a path that leads to state j leaving from state i with positive probability
● Data Source:
CranContrib
● Keywords:
● Alias: is.accessible
●
0 images
|
|
Function to evaluate the prior probability of a transition matrix. It is based on conjugate priors and therefore a Dirichlet distribution is used to model the transitions of each state.
● Data Source:
CranContrib
● Keywords:
● Alias: priorDistribution
●
0 images
|
Provided any markovchain or markovchainList objects, it returns a sequence of states coming from the underlying stationary distribution.
● Data Source:
CranContrib
● Keywords:
● Alias: markovchainSequence, rmarkovchain
●
0 images
|
|
Fit a markovchainList
● Data Source:
CranContrib
● Keywords:
● Alias: markovchainListFit
●
0 images
|
The S4 class that describes HigherOrderMarkovChain objects.
● Data Source:
CranContrib
● Keywords:
● Alias: HigherOrderMarkovChain-class
●
0 images
|
|
It extracts the conditional distribution of the subsequent state, given current state.
● Data Source:
CranContrib
● Keywords:
● Alias: conditionalDistribution
●
0 images
|
|
The transition matrix of the embedded DTMC is inferred from the CTMC's generator.
● Data Source:
CranContrib
● Keywords:
● Alias: generatorToTransitionMatrix
●
0 images
|
providing 
.