transitions in R

Hi, All.  I'd have a set of data in an array:

process <- c( 5 , 7 , 4 , 1 , 4 , 1 , 4 , 1 , 4 , 4 , 1 , 5 , 4 , ...)

and I'd like to know the number of transitions in this data.  I
calculate transitions as the number of times a number follows another
number.  thus, something like this would be a 1 deep transition:

1 --> 1 : 10% (and actual number of 1 --> 1 occurrences)
1 --> 2 : 2%
1 --> 3 : 23%
...
2 --> 1 : 2%
2 --> 2 : 8%
(etc.)

of course, you can have 2 or 3 or n deep transitions, but I'm really
only interested in 1 and 2 (and maybe 3) deep transitions.

what is the best way of calculating this info in R?

One way is to just tabulate the process against an offset of itself

process <- c( 5 , 7 , 4 , 1 , 4 , 1 , 4 , 1 , 4 , 4 , 1 , 5 , 4 )
n<-length(process)
table(process[-1],process[-n])

1 4 5 7
  1 0 4 0 0
  4 3 1 1 1
  5 1 0 0 0
  7 0 0 1 0

Or if you now want to divide each column by its sum and get %ages

tt<-table(process[-1],process[-n])
sweep(tt,2,apply(tt,2,sum),"/")*100

1  4  5   7
  1  0 80  0   0
  4 75 20 50 100
  5 25  0  0   0
  7  0  0 50   0


	-thomas

Thomas Lumley			Asst. Professor, Biostatistics
tlumley at u.washington.edu	University of Washington, Seattle

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Hi, All.  I'd have a set of data in an array:

process <- c( 5 , 7 , 4 , 1 , 4 , 1 , 4 , 1 , 4 , 4 , 1 , 5 , 4 , ...)

and I'd like to know the number of transitions in this data.  I
calculate transitions as the number of times a number follows another
number.  thus, something like this would be a 1 deep transition:

1 --> 1 : 10% (and actual number of 1 --> 1 occurrences)
1 --> 2 : 2%
1 --> 3 : 23%
...
2 --> 1 : 2%
2 --> 2 : 8%
(etc.)

of course, you can have 2 or 3 or n deep transitions, but I'm really
only interested in 1 and 2 (and maybe 3) deep transitions.

what is the best way of calculating this info in R?

thanks!
greg

transitions <- function(vect, t1, t2) {
  # vect is the vector to test
  # t1 is the vector of all initial states of the transitions
  # t2 is the vector of all final states of the transitions
  n <- length(vect)
  nt <- length(t1)   # rem: t2 must be same length, not tested here
  v <- rep(vect, nt)
  dim(v) <- c(n, nt)
  v <- t(v)
  tests <- (v[, 1:(n-1)]==t1 & v[, 2:n]==t2)
  res <- apply(tests, 1, "sum", na.rm=T)
  res
}

p <- c(1,2,3,2,1,1,2,1,3)
transitions(p, c(1,1,1,2,2,2), c(1,2,3,1,2,3))

[1] 1 2 1 2 0 1


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