Question

I am running a coin-toss simulation with a loop which runs about 1 million times.

Each time I run the loop I wish to retain the table output from the RLE command. Unfortunately a simple append does not seem to be appropriate. Each time I run the loop I get a slightly different amount of data which seems to be one of the sticking points.

This code gives an idea of what I am doing:

N <- 5 #Number of times to run
rlex <-NULL
#begin loop#############################
for (i in 1:N) { #tells R to repeat N number
x <-sample(0:1, 100000, 1/2)
rlex <-append(rlex, rle(x))
}
table(rlex) #doesn't work
table(rle(x)) #only 1

So instead of having five separate rle results (in this simulation, 1 million in the full version), I want one merged rle table. Hope this is clear. Obviously my actual code is a bit more complex, hence any solution should be as close to what I have specified as possible.

UPDATE: The loop is an absolute requirement. No ifs or buts. Perhaps I can pull out the table(rle(x)) data and put it into a matrix. However again the stumbling block is the fact that some of the less frequent run lengths do not always turn up in each loop. Thus I guess I am looking to conditionally fill a matrix based on the run length number?

Last update before I give up: Retaining the rle$values will mean that too much data is being retained. My simulation is large-scale and I really only wish to retain the table output of the rle. Either I retain each table(rle(x)) for each loop and combine by hand (there will be thousands), or I find a programmatic way to keep the data (yes for zeroes and ones) and have one table that is formed from merging each of the individual loops as I go along.

Either this is easyish to do, as specified, or I will not be doing it. It may seem a silly idea/request, but that should be incidental to whether it can be done.

Seriously last time. Here is an animated gif showing what I expect to happen.

After each iteration of the loop data is added to the table. This is as clear as I am going to be able to communicate it.

Answer 1

OK, attempt number 4:

N <- 5
set.seed(1)
x <- NULL
for (i in 1:N){
  x <- rbind(x, table(rle(sample(0:1, 100000, replace=TRUE))))
}

x <- as.data.frame(x)
x$length <- as.numeric(rownames(x))
aggregate(x[, 1:2], list(x[[3]]), sum)

Produces:

   Group.1     0     1
1        1 62634 62531
2        2 31410 31577
3        3 15748 15488
4        4  7604  7876
5        5  3912  3845
6        6  1968  1951
7        7   979   971
8        8   498   477
9        9   227   246
10      10   109   128
11      11    65    59
12      12    24    30
13      13    21    11
14      14     7    10
15      15     0     4
16      16     4     2
17      17     0     1
18      18     0     1

---

If you want the aggregation inside the loop, do:

N <- 5
set.seed(1)
x <- NULL
for (i in 1:N){
  x <- rbind(x, table(rle(sample(0:1, 100000, replace=TRUE))))
  y <- aggregate(x, list(as.numeric(rownames(x))), sum)
  print(y)
}