Erratic seed behavior with rbinom(prob=0.5) in R

Question

I have found what I would consider erratic behavior (but for which I hope there is a simple explanation) in R\'s use of seeds in conjunction with rbinom()

Answer 1

So let's turn our comments into an answer. Thanks to Ben Bolker for putting us on the right track with a link to the code: https://svn.r-project.org/R/trunk/src/nmath/rbinom.c and the suggestion to track down where unif_rand() is called.

A quick scan and it seems that the code is broken into two sections, delimited by the comments:

/*-------------------------- np = n*p >= 30 : ------------------- */

and

/*---------------------- np = n*p < 30 : ------------------------- */

Inside each of these, the number of calls to unif_rand is not the same (two versus one.)

So for a given size (n), your random seed may end up in a different state depending on the value of prob (p): whether size * prob >= 30 or not.

With that in mind, all the results you got with your examples should now make sense:

# these end up in the same state
rbinom(n=1,size=60,prob=0.4) # => np <  30
rbinom(n=1,size=60,prob=0.3) # => np <  30

# these don't
rbinom(n=1,size=60,prob=0.5) # => np >= 30
rbinom(n=1,size=60,prob=0.3) # => np <  30

# these don't
{rbinom(n=1,size=60,prob=0.5)  # np >= 30
 rbinom(n=1,size=50,prob=0.3)} # np <  30
{rbinom(n=1,size=60,prob=0.1)  # np <  30
 rbinom(n=1,size=50,prob=0.3)} # np <  30

# these do
{rbinom(n=1,size=60,prob=0.3)  # np <  30
 rbinom(n=1,size=50,prob=0.5)} # np <  30
{rbinom(n=1,size=60,prob=0.1)  # np <  30
 rbinom(n=1,size=50,prob=0.3)} # np <  30