Exactly, from ?.Random.seed:
"In the underlying C, .Random.seed[-1] is unsigned; therefore in R
.Random.seed[-1] can be negative, due to the representation of an
unsigned integer by a signed integer. "
and
"It can be saved and restored, but should not be altered by the user. "
Best,
Uwe Ligges
On 09.01.2020 16:40, Jeff Newmiller wrote:
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 ...
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