I am no expert on this specific algorithm, but there is no "32-bit unsigned
integer" type in R. Presumably the interpretation of those negative numbers in
the C code is as if they were unsigned while R presents them as if they were
signed because it cannot do otherwise.
AFAIK you need to use set.seed to configure .Random.seed, and you can retrieve
and later restore the vectors created this way in the future. As I understand
it there exist invalid vectors that cannot arbitrarily be used by this
algorithm so generating them yourself is at the very least hard, and possibly
could break in future versions of R.
On January 9, 2020 1:18:01 AM PST, Luca Passalacqua via R-help
<r-help@r-project.org> wrote:
>Dear R users,
>
> inspecting .Random.seed for the Mersenne Twister (MT) I find (many)
>negative values for the
>624 values of the initial state of the generator.
>It seems to me that this is a bug (an unsigned integer mapped to a
>signed
>integer ?),
>since, to my understanding, the R version of MT should be working with
>32-bits unsigned long.
>Moreover, this prevents starting the generator by setting .Random.seed
>to
>user provided
>values.
>Could someone please provide some insight to this issue ?
>Many thanks,
>
>Luca Passalacqua
>
>
>> RNGkind('default')> RNGkind()[1] "Mersenne-Twister" "Inversion"
>> set.seed(1)> .Random.seed [1] 403 624 -169270483
>-442010614 -603558397 ...
--
Sent from my phone. Please excuse my brevity.
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