Try comparing the streams for when the 625-integer versions of the seeds are identical. (R's seed is 626 integers: omit the first value, which indicates which random number generator the seed is for.). I find the the MKL Mersenne Twister results match R's (with occassional differences in the last bit) when the 625-integer seeds the same.
I believe R fiddles with the single-integer seed to spread it out a bit. S's seed was taken modulo 1024 so old users tended not use use single-seeds bigger than 1023. Bill Dunlap TIBCO Software wdunlap tibco.com On Tue, Aug 30, 2016 at 2:45 PM, Mark Roberts <ersatz....@gmail.com> wrote: > Whomever, > > I recently sent the "bug report" below tor-c...@r-project.org and have > just been asked to instead submit it to you. > > Although I am basically not an R user, I have installed version 3.3.1 > and am also the author of a statistics program written in Visual Basic > that contains a component which correctly implements the Mersenne > Twister (MT) algorithm. I believe that it is not possible to generate > the correct stream of pseudorandom numbers using the MT default random > number generator in R, and am not the first person to notice this. Here > is a posted 2013 entry > (www.r-bloggers.com/reproducibility-and-randomness/) on an R website > that asserts that the SAS computer program implementation of the MT > algorithm produces different numbers than R does when using the same > starting seed number. The author of this post didn’t get anyone to > respond to his query about the reason for this SAS vs. R discrepancy. > > There are two ways of initializing the original MT computer program > (written in C) so that an identical stream of numbers can be repeatedly > generated: 1) with a particular integer seed number, and 2) with a > particular array of integers. In the 'compilation and usage' section > of this webpage (https://github.com/cslarsen/mersenne-twister) there is > a listing of the first 200 random numbers the MT algorithm should > produce for seed number = 1. The inventors of the Mersenne Twister > random number generator provided two different sets of the first 1000 > numbers produced by a correctly coded 32-bit implementation of the MT > algorithm when initializing it with a particular array of integers at: > www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/CODES/mt19937ar.out. > [There is a link to this output at: > www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/emt19937ar.html.] > > My statistics program obtains exactly those 200 numbers from the first > site mentioned in the previous paragraph and also obtains those same > numbers from the second website (though I didn't check all 2000 values). > Assuming that the MT code within R uses the 32-bit MT algorithm, I > suspect that the current version of R can't do that. If you (i.e., > anyone who might knowledgeably respond to this report) is able to > duplicate those reference test-values, then please send me the R code to > initialize the MT code within R to successfully do that, and I apologize > for having wasted your time. If you (collectively) can't do that, then R > is very likely using incorrectly implemented MT code. And if this > latter possibility is true, it seems to me that this is something that > should be fixed. > > Mark Roberts, Ph.D. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel [[alternative HTML version deleted]] ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
