R/fittingFunctions.R
markovchainSequence.Rd
Provided any markovchain
object, it returns a sequence of
states coming from the underlying stationary distribution.
markovchainSequence( n, markovchain, t0 = sample(markovchain@states, 1), include.t0 = FALSE, useRCpp = TRUE )
n | Sample size |
---|---|
markovchain |
|
t0 | The initial state |
include.t0 | Specify if the initial state shall be used |
useRCpp | Boolean. Should RCpp fast implementation being used? Default is yes. |
A Character Vector
A sequence of size n is sampled.
A First Course in Probability (8th Edition), Sheldon Ross, Prentice Hall 2010
Giorgio Spedicato
# 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 <- markovchainSequence(n = 100, markovchain = mcB, t0 = "a")