markovchain (version 0.0.9.5)

rmarkovchain: Function to generate a sequence of states from homogeneous or non-homogeneous Markov chains.

Description

Provided any markovchain or markovchainList objects, it returns a sequence of states coming from the underlying stationary distribution.

Usage

rmarkovchain(n, object, ...)
markovchainSequence(n, markovchain, t0 = sample(markovchain@states, 1), 
include.t0 = FALSE)

Arguments

n

Sample size

object

Either a markovchain or a markovchainList object.

...

additional parameters passed to the internal sampler

markovchain

The markovchain object

t0

The initial state.

include.t0

Specify if the initial state shall be used.

Value

• Either a character vector or a data frame

Details

When an homogeneous process is assumed (markovchain object) a sequence is sampled of size n. When an non - homogeneous process is assumed, n samples are taken but the process is assumed to last from the begin to the end of the non-homogeneous markov process.

References

A First Course in Probability (8th Edition), Sheldon Ross, Prentice Hall 2010

See Also

markovchainFit

Examples

#define the Markov chain
statesNames=c("a","b","c")
mcB<-new("markovchain", states=statesNames, transitionMatrix=matrix(c(0.2,0.5,0.3,
0,0.2,0.8,0.1,0.8,0.1),nrow=3, byrow=TRUE, dimnames=list(statesNames,statesNames)
                 ))
#show the sequence
outs<-markovchainSequence(n=100,markovchain=mcB, t0="a")
outs2<-rmarkovchain(n=20, object=mcB)