[Rd] Seeding non-R RNG with numbers from R's RNG stream

[Tommy Jones]

Thank you for this. I'd like to be sure I understand the
intuition correctly. Is the following true from what you said?

I can just fix the seed at the C++ level and the results will still be
(pseudo) random because the initialization at the R level is (pseudo)
random.

On Thu, Jul 30, 2020 at 3:36 PM Duncan Murdoch <murdoch.duncan using gmail.com>
wrote:

> I wouldn't trust the C++ generator to be as good if you seed it this way
> as if you just seeded it once with your phone number (or any other fixed
> value) and let it run, because it's probably never been tested to be
> good when run this way.  Is it good enough for the way you plan to use
> it?  Maybe.
>
> Duncan Murdoch
>
> On 30/07/2020 3:05 p.m., Tommy Jones wrote:
> > Hi,
> >
> > I am constructing a function that does sampling in C++ using a non-R RNG
> > stream for thread safety reasons. This C++ function is wrapped by an R
> > function, which is user facing. The R wrapper does some sampling itself
> to
> > initialize some variables before passing them off to C++. So that my
> users
> > do not have to manage two mechanisms to set random seeds, I've
> constructed
> > a solution (shown below) that allows both RNGs to be seeded with set.seed
> > and respond to the state of R's RNG stream.
> >
> > I believe the below works. However, I am hoping to get feedback from more
> > experienced useRs as to whether or not the below approach is unsafe in
> ways
> > that may affect reproducibility, modify global variables in bad ways, or
> > have other unintended consequences I have not anticipated.
> >
> > Could I trouble one or more folks on this list to weigh in on the safety
> > (or perceived wisdom) of using R's internal RNG stream to seed an RNG
> > external to R? Many thanks in advance.
> >
> > This relates to a Stackoverflow question here:
> >
> https://stackoverflow.com/questions/63165955/is-there-a-best-practice-for-using-non-r-rngs-in-rcpp-code
> >
> > Pseudocode of a trivial facsimile of my current approach is below.
> >
> > --Tommy
> >
> > sample_wrapper <- function() {
> >    # initialize a variable to pass to C++
> >    init_var <- runif(1)
> >
> >    # get current state of RNG stream
> >    # first entry of .Random.seed is an integer representing the
> algorithm used
> >    # second entry is current position in RNG stream
> >    # subsequent entries are pseudorandom numbers
> >    seed_pos <- .Random.seed[2]
> >
> >    seed <- .Random.seed[seed_pos + 2]
> >
> >    out <- sample_cpp(init_var = init_var, seed = seed)
> >
> >    # move R's position in the RNG stream forward by 1 with a throw away
> sample
> >    runif(1)
> >
> >    # return the output
> >    out}
> >
> >       [[alternative HTML version deleted]]
> >
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> >
>
>

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