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

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

rmarkovchain(
  n,
  object,
  what = "data.frame",
  useRCpp = TRUE,
  parallel = FALSE,
  num.cores = NULL,
  ...
)

Arguments

n: Sample size
object: Either a markovchain or a markovchainList object
what: It specifies whether either a data.frame or a matrix (each rows represent a simulation) or a list is returned.
useRCpp: Boolean. Should RCpp fast implementation being used? Default is yes.
parallel: Boolean. Should parallel implementation being used? Default is yes.
num.cores: Number of Cores to be used
...: additional parameters passed to the internal sampler

Value

Character Vector, data.frame, list or matrix

Details

When a homogeneous process is assumed (markovchain object) a sequence is sampled of size n. When a 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.

Note

Check the type of input

References

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

Author

Giorgio Spedicato

Examples

# define the markovchain object
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 <- rmarkovchain(n = 100, object = mcB, what = "list")


#define markovchainList object
statesNames <- c("a", "b", "c")
mcA <- 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)))
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)))
mcC <- 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)))
mclist <- new("markovchainList", markovchains = list(mcA, mcB, mcC)) 

# show the list of sequence
rmarkovchain(100, mclist, "list")
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