Markov chain simulation

For small transistion matrices (which seems to be what you ask for), 
something like this:

P <- matrix( c(0.2, 0.5, 0.5, 0.1, 0.8, 0.1, 

+               0.2, 0.1, 0.7), 3,3, byrow=TRUE)

simMarkov <- function( P, len=1000) {

+        n <- NROW(P)
+        result <- numeric(len)
+        result[1] <- 1
+        for (i in 2:len) {
+            result[i] <- sample(1:n, 1, prob=P[ result[i-1], ])
+        }
+        result
+ }

muestra <- simMarkov(P)

Note that this assumes the initial state to be 1, easy to modify wuth 
an extra argument to simMarkov.

Whe seeing a for-loop solution as above, it is natural to ask for a 
vectorized solution. But whith the FUNction within the loop using 
earlier results, that seems difficult.

Kjetil Halvorsen

Hi,

Does anybody know a function to simulate a Markov chain given a 
probability transition matrix and an initial state ?
Thanks.

Philippe
-- 

--------------------------------------------------

Philippe Hup?
Institut Curie - Equipe Bioinformatique
26, rue d'Ulm - 75005 PARIS France
+33 (0)1 42 34 65 29

Philippe.Hupe at curie.fr <mailto:Philippe.Hupe at curie.fr>

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