[Rd] limitations to random number generator in 64-bits machines
Prof Brian Ripley
ripley at stats.ox.ac.uk
Fri Feb 22 12:54:45 CET 2013
On 22/02/2013 11:02, Bert Gunter wrote:
> AFAICS, these are statistics, not R, issues, and are completely off
> topic here. You should post on a statistics list, such as
> stats.stackexchange.com, instead.
Except for the unattributed vague comment about 64-bit (sic) machines.
The RNG is the same (and gives the same results) on both 32- and 64-bit
machines. The size of the pointer has nothing to do with random-number
generation.
>
> Cheers,
> Bert
>
> On Thu, Feb 21, 2013 at 5:20 AM, Mauricio Zambrano-Bigiarini
> <mauricio.zambrano at jrc.ec.europa.eu> wrote:
>> Dear List,
>>
>> Recently I got the comment that the implementation of the random number
>> generator used by default in R (Mersenne-Twister) could not be "safe" for
>> 64-bits machines, so I decided to put the question here because I do not
>> have expertise in that topic, and because this question could be "too
>> technical for R-help's audience". I apologise if this is not the case.
>>
>> The period 2^19937 - 1 mentioned in the help page of 'RNG' for the
>> Mersenne-Twister generator, is it the same for 32-bits machines and 64-bits
>> ones ?
>>
>> In addition:
>>
>> -) If I want to generate two consecutive sequences s_1 and s_2 of n
>> pseudo-random numbers each, and knowing how the Random number generator is
>> coded, can we estimate in advance the correlation coefficient rho between s1
>> and s2?
>>
>> -) Let us say that we compute the correlation coefficient rho between s_1
>> and s_2 and find it is not null. How small should it be so that we can
>> reasonably use a statistical analysis that does suppose that the sequences
>> are independent ?
>>
>>
>> Thank in advance for any help you can provide,
>>
>> Mauricio Zambrano-Bigiarini
>>
>> --
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>> Institute for Environment and Sustainability (IES)
>> Joint Research Centre (JRC), European Commission
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>>
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>
>
>
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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