[R] Pre-allocation of matrices is LESS efficient?

[Alex F. Bokov]

Motivation: during each iteration, my code needs to collect tabular data (and use it only during that iteration), but the rows of data may vary. I thought I would speed it up by preinitializing the matrix that collects the data with zeros to what I know to be the maximum number of rows. I was surprised by what I found...

# set up (not the puzzling part)
x<-matrix(runif(20),nrow=4); y<-matrix(0,nrow=12,ncol=5); foo<-c();

# this is what surprises me... what the?
> system.time(for(i in 1:100000){n<-sample(1:4,1);y[1:n,]<-x[1:n,];});
   user  system elapsed 
  1.510   0.000   1.514 
> system.time(for(i in 1:100000){n<-sample(1:4,1);foo<-x[1:n,];});
   user  system elapsed 
  1.090   0.000   1.085

These results are very repeatable. So, if I'm interpreting them correctly, dynamically allocating 'foo' each time to whatever the current output size is runs faster than writing to a subset of a preallocated 'y'? How is that possible?

And, more generally, I'm sure other people have encountered this type of situation. Am I reinventing the wheel? Is there a best practice for storing temporary loop-specific data?

Thanks.

PS:  By the way, though I cannot write to foo[,] because the size is different each time, I tried writing to foo[] and the runtime was worse than either of the above examples.