Issue with aggregate.ts and/or %\% on Windows

Patrick Aboyoun wrote:

I've stumbled across an issue with aggregate.ts that either is due to a
misuse of %/% or something deeper relating to numerical precision on
Windows. The test code is

x <- rep(6:10, 1:5)
as.vector(aggregate(as.ts(x), FUN = mean, ndeltat = 5))

On Linux and Mac I get the correct answer

x <- rep(6:10, 1:5)
as.vector(aggregate(as.ts(x), FUN = mean, ndeltat = 5)

[1]  7.2  8.8 10.0

sessionInfo()

R version 2.11.0 RC (2010-04-18 r51771)
i386-apple-darwin9.8.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base


and on Windows I get an incorrect answer

x <- rep(6:10, 1:5)
as.vector(aggregate(as.ts(x), FUN = mean, ndeltat = 5))

[1] 7.0 8.5 9.5

sessionInfo()

R version 2.11.0 beta (2010-04-11 r51685)
i386-pc-mingw32

locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base


Walking through the aggregate.ts code I found this difference is due to
what 1 %/% 0.2 produces on the different platforms.

On Mac and Linux I get

1 %/% 0.2

[1] 5

and on Windows I get

1 %/% 0.2

[1] 4


I don't know if %/% supports floating point operands so I'm not sure how
to report this issue, but here it is anyway.

It's not as straightforward as that. I get 4 on one (32 bit) Linux, and
5 on another (64 bit). Based on samples of size one, I wouldn't want to
conjecture that "bitness" is the root cause, but it is probably not the
OS per se, rather the CPU or compiler version.

It is even more insidious: I see on the SAME system

1%/%0.2

[1] 4

1/0.2==5

[1] TRUE

so it isn't just the usual precision issue.

Of course, exact calculations with floating-point numbers is "unsafe at
any speed",  but this is quite peculiar. Presumably, it comes about
because of intermediate storage in an extended precision register.


-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com