[R] What's the BEST way in R to adapt this vector?

[zerfetzen]

Goal:
Suppose you have a vector that is a discrete variable with values ranging
from 1 to 3, and length of 10.  We'll use this as the example:

y <- c(1,2,3,1,2,3,1,2,3,1)

...and suppose you want your new vector (y.new) to be equal in length to the
possible discrete values (3) times the length (10), and formatted in such a
way that if y[1] == 1, then y.new[1:3] == c(1,0,0), and if y[2] == 2, then
y.new[4:6] == c(0,1,0).  For example, the final goal should be:

y.new <- c(1,0,0,0,1,0,0,0,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,0,0,0,1,1,0,0)

Note: I know how to do this with loops, but that's not taking advantage of
R's capabilities with vectors and, I suspect, matrices.

So far, here's my best:

y <- c(1,2,3,1,2,3,1,2,3,1)
y.k <- length(unique(y)) #Num. of Categories of y
y.n <- NROW(y)
y.nk <- y.n * y.k #Length of new vector
y.1 <- ifelse(y == 1,1,0)
y.2 <- ifelse(y == 2,1,0)
y.3 <- ifelse(y == 3,1,0)
z <- cbind(y.1, y.2, y.3)
z.trans <- t(z)
y.new <- c(1:y.nk); y.new[1:y.nk] <- NA
y.new <- as.vector(z.trans)
rm(y.k, y.n, y.nk, y.1, y.2, y.3, z, z.trans)
y
y.new

Is there a better a way?  I'm still pretty new.  Thanks.
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