Add dqrrademacher

[kylebutts]

In statistics, a lot of methods require drawing Rademacher weights, -1 and 1, with probably 1/2 each (e.g. bootstrapping and approximations). To minimize the number of random numbers needed, I draw random 64 bits and use each bit of the integer (which is 0/1 with equal probability) and uses that as a 0/1 variable. It's about 8x as fast as dqrng::sample(c(-1, 1))!

I believe I fixed the segfault (user error on 0-based indexing in C++ 🤦🏼‍♂️). I tested for segfaults by calling the following and nothing came-up, so I think we're good.

lapply(1:1000, function(i) dqrrademacher(1e7))
dqrrademacher(1e9)

---

Benchmarks

library(dqrng)
library(rademacher)
n = 1e7
bench::mark(
  dqrrademacher = dqrrademacher(n),
  rademacher = rademacher::sample_rademacher(n),
  runif = (stats::runif(n) > 0.5) * 2 - 1,
  samp = sample(x = c(1, -1), size = n, replace = TRUE),
  dqsamp = dqsample(x = c(1,-1), size = n, replace = TRUE),
  check = FALSE
)
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
#> # A tibble: 5 × 6
#>   expression         min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>    <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 dqrrademacher   4.59ms   5.44ms    187.      38.1MB    91.4 
#> 2 rademacher      5.69ms    6.7ms    135.      39.4MB    53.8 
#> 3 runif          88.62ms  91.13ms     10.8    190.7MB    12.6 
#> 4 samp          105.22ms 109.35ms      9.23   114.4MB     7.38
#> 5 dqsamp         45.01ms  48.31ms     20.7    114.5MB    16.9

^{Created on 2023-07-01 with reprex v2.0.2}

[rstub]

BTW, the checks via GHA are currently failing, because I need to add some changes from #47. If you don't mind I would cherry pick those changes into this PR.

[rstub]

LGTM! Do you want to add yourself as contributor in DESCRIPTION?

[kylebutts]

Great, Just added myself! Thanks for your help Ralf!

[rstub]

Thanks for the contribution! It will take a while until this makes its way to CRAN, since I want to finish #47 first. In the meantime, it should soon be available from https://daqana.r-universe.dev/dqrng.