Displaying 2 results from an estimated 2 matches for "n_itr".
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2018 Sep 21
1
Bias in R's random integers?
...good since we often have
to get a second random number:
> bench::mark(orig = sample.int(m, 1000000, replace = TRUE),
+ new = sample_int(m, 1000000, replace = TRUE),
+ check = FALSE)
# A tibble: 2 x 14
expression min mean median max `itr/sec` mem_alloc n_gc n_itr
<chr> <bch:t> <bch:t> <bch:t> <bch> <dbl> <bch:byt> <dbl> <int>
1 orig 8.15ms 8.67ms 8.43ms 10ms 115. 3.82MB 4 52
2 new 25.21ms 25.58ms 25.45ms 27ms 39.1 3.82MB 2 18
# ... with 5 more va...
2018 Sep 20
5
Bias in R's random integers?
On 9/20/18 1:43 AM, Carl Boettiger wrote:
> For a well-tested C algorithm, based on my reading of Lemire, the unbiased
> "algorithm 3" in https://arxiv.org/abs/1805.10941 is part already of the C
> standard library in OpenBSD and macOS (as arc4random_uniform), and in the
> GNU standard library. Lemire also provides C++ code in the appendix of his
> piece for both this and