| simulateMarkovChain {spgs} | R Documentation |
Simulate a first-Order Markov Chain
Description
Simulates a first-order Markov chain.
Usage
simulateMarkovChain(n, trans.mat, init.dist=NULL, states=colnames(trans.mat))
Arguments
n |
the length of the sample path to simulate. |
trans.mat |
The transition matrix of the Markov chain to simulate. |
init.dist |
The initial distribution to use for starting the simulation. If it is not specified, the stationary distribution of the Markov chain will be computed from trans.mat and used to start the simulation in the steady state. |
states |
This argument can be used to override the labels on the transition matrix (if any) and name the states output on the sample path. |
Details
‘trans.mat’ must be a stochastic matrix. It must either have both row and
column names, in which case they must agree, or no row and column names at all.
The row/column names will be used to label the states visited by the Markov
chain in the sample path simulated. If ‘states’ is specified, it will be
used to label the states of the Markov chain instead of the row/column names of
‘trans.mat’, in which the length of ‘states’ must agree with the
dimension of ‘trans.mat’. If ‘trans.mat’ has no row/column names and
‘states’ is not specified, then the states of the Markov chain will be
labelled 1,\ldots,n, where n is the dimension of ‘trans.mat’.
Value
A vector of length n containing a realisation of the specified Markov chain.
Author(s)
Andrew Hart and Servet MartÃnez
See Also
estimateMarkovChain, rstochmat, rcspr2mat
Examples
simulateMarkovChain(50, matrix(c(.8, .2, .2, .8), ncol=2))
simulateMarkovChain(50, rstochmat(3), states=c("yes", "no", "maybe"))