R Language Random Numbers Generator Random number generator's reproducibility


Example

When expecting someone to reproduce an R code that has random elements in it, the set.seed() function becomes very handy. For example, these two lines will always produce different output (because that is the whole point of random number generators):

> sample(1:10,5)
[1]  6  9  2  7 10
> sample(1:10,5)
[1]  7  6  1  2 10

These two will also produce different outputs:

> rnorm(5)
[1]  0.4874291  0.7383247  0.5757814 -0.3053884  1.5117812
> rnorm(5)
[1]  0.38984324 -0.62124058 -2.21469989  1.12493092 -0.04493361

However, if we set the seed to something identical in both cases (most people use 1 for simplicity), we get two identical samples:

> set.seed(1)
> sample(letters,2)
[1] "g" "j"
> set.seed(1)
> sample(letters,2)
[1] "g" "j"

and same with, say, rexp() draws:

> set.seed(1)
> rexp(5)
[1] 0.7551818 1.1816428 0.1457067 0.1397953 0.4360686
> set.seed(1)
> rexp(5)
[1] 0.7551818 1.1816428 0.1457067 0.1397953 0.4360686