[R] cbind in a loop...better way?

[Evan Cooch]

...or some such. I'm trying to work up a function wherein the user 
passes a list of matrices to the function, which then (1) takes each 
matrix, (2) performs an operation to 'vectorize' the matrix (i.e., given 
an (m x n) matrix x, this produces the vector Y of length  m*n that 
contains the columns of the matrix x, stacked below each other), and 
then (3) cbinds them together.

Here is an example using the case where I know how many matrices I need 
to cbind together. For this example, 2 square (3x3) matrices:

  a <- matrix(c,0,20,50,0.05,0,0,0,0.1,0),3,3,byrow=T)
  b <- matrix(c(0,15,45,0.15,0,0,0,0.2,0),3,3,byrow=T)

I want to vec them, and then cbind them together. So,

result  <- cbind(matrix(a,nr=9), matrix(b,nr=9))

which yields the following:

       [,1]  [,2]
  [1,]  0.00  0.00
  [2,]  0.05  0.15
  [3,]  0.00  0.00
  [4,] 20.00 15.00
  [5,]  0.00  0.00
  [6,]  0.10  0.20
  [7,] 50.00 45.00
  [8,]  0.00  0.00
  [9,]  0.00  0.00

Easy enough. But, I want to put it in a function, where the number and 
dimensions  of the matrices is not specified. Something like

Using matrices (a) and (b) from above, let

   env <- list(a,b).

Now, a function (or attempt at same) to perform the desired operations:

   vec=function(matlist) {

       n_mat=length(matlist);
       size_mat=dim(matlist[[1]])[1];

       result=cbind()

        for (i in 1:n_mat) {
          result=cbind(result,matrix(matlist[[i]],nr=size_mat^2))
                           }

      return(result)

    }


When I run vec(env), I get the *right answer*, but I am wondering if 
there is a *better* way to get there from here than the approach I use 
(above). I'm not so much interested in 'computational efficiency' as I 
am in stability, and flexibility.

Thanks...