[Rd] Strange Behavior in RNG

[Ben Bolker]

You could argue that the 'n' argument should be rounded rather than
truncated, but this form of coercion from float to integer is
common/standard (in C, for example). In any case, it's a long standing part
of R and is very unlikely to be changed ...

On Sat, Aug 17, 2024, 12:11 AM Jiefei Wang <szwjf08 using gmail.com> wrote:

> Hi Rui and John,
>
> Thanks for your reply. I'm not sure if this is a question for R-help as I
> think the behavior of RNG is weird, but I will happy to move this
> discussion if the admin think this is not their topic.
>
> I was a C/C++ developer so I understand the double-type numbers sometimes
> can generate surprising results, but what unexpected here is that even the
> number is super close to 400 'rnorm' still rounds it down to 399. Shouldn't
> it be round up in this case? Probably the underlying code just convert the
> number into an int type, but I was expecting that the function can tolerate
> a certain degree of errors. Maybe I have too much expectations for it...
>
> Best,
> Jiefei
>
>
>
> On Fri, Aug 16, 2024, 22:19 Rui Barradas <ruipbarradas using sapo.pt> wrote:
>
> > Às 01:45 de 17/08/2024, Jiefei Wang escreveu:
> > > Hi,
> > >
> > > I just observed a strange behavior in R. The rnorm function does not
> > > give me the numbers with a given length. I think it is somehow related
> > > to the internal representation of double-type numbers but I am not
> > > sure if this is supposed to happen. Below is a reproducible example
> > >
> > > ```
> > > ## Create a list, we will only take the forth value, which is 0.6
> > > nList <- seq(0,1,0.2)
> > > n <- nList[4]
> > > n
> > > # [1] 0.6
> > > length(rnorm(1000*n))
> > > # [1] 600
> > > length(rnorm(1000-1000*n))
> > > # [1] 399 <--- What happened here?
> > > length(rnorm(1000-1000*0.6))
> > > # [1] 400
> > > 1000-1000*n
> > > # [1] 400 <- this looks good to me...
> > > 1000-1000*0.6
> > > # [1] 400
> > > identical(n, 0.6)
> > > # [1] FALSE
> > > .Internal(inspect(n))
> > > # @0x00000217c75d79d0 14 REALSXP g0c1 [REF(1)] (len=1, tl=0) 0.6
> > > .Internal(inspect(0.6))
> > > # @0x00000217c791e0c8 14 REALSXP g0c1 [REF(2)] (len=1, tl=0) 0.6
> > > ```
> > >
> > > As you can see, length(rnorm(1000-1000*n)) does not really give me the
> > > result I want. This is somewhat surprising because it is hard to
> > > imagine that a manually-typed 0.6 can behave differently than 0.6 from
> > > a sequence. Furthermore, 0.6 is the only problematic number from
> > > `nList`. The rest numbers work fine. I can guess it is due to the
> > > rounding mechanism, but I think this should be treated as a bug: if
> > > the print function can show the result of 1000-1000*n correctly, it
> > > will be strange that rnorm behaves differently. Below is my session
> > > info
> > >
> > > R version 4.3.0 (2023-04-21 ucrt)
> > > Platform: x86_64-w64-mingw32/x64 (64-bit)
> > > Running under: Windows 10 x64 (build 19045)
> > >
> > > Matrix products: default
> > >
> > > locale:
> > > [1] LC_COLLATE=English_United States.utf8
> > > [2] LC_CTYPE=English_United States.utf8
> > > [3] LC_MONETARY=English_United States.utf8
> > > [4] LC_NUMERIC=C
> > > [5] LC_TIME=English_United States.utf8
> > >
> > > time zone: America/Chicago
> > > tzcode source: internal
> > >
> > > ______________________________________________
> > > R-devel using r-project.org mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-devel
> > Hello,
> >
> > This is R FAQ 7.31.
> > In fact, the sequences
> >
> > seq(0, 1, 0.1)
> > seq(0, 1, 0.2)
> >
> > should probably be a FAQ 7.31 example.
> > If you print the numbers with more decimals you will see why the error.
> >
> >
> >
> > # generate the list
> > nList <- seq(0,1,0.2)
> > # compare the list with manually typed numbers
> > nList != c(0, 0.2, 0.4, 0.6, 0.8, 1)
> > #> [1] FALSE FALSE FALSE  TRUE FALSE FALSE
> >
> > # note the value of 0.6
> > print(nList, digits = 16L)
> > #> [1] 0.0000000000000000 0.2000000000000000 0.4000000000000000
> > 0.6000000000000001
> > #> [5] 0.8000000000000000 1.0000000000000000
> >
> >
> > Hope this helps,
> >
> > Rui Barradas
> >
> >
> >
> > --
> > Este e-mail foi analisado pelo software antivírus AVG para verificar a
> > presença de vírus.
> > www.avg.com
> >
>
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