On 18/02/2009 12:41 PM, Stavros Macrakis wrote:
Hmm. Why not use the same method to guarantee the same result? Or at
least document the possibility that cumsum(x)[length(x)] != sum(x)...
that seems like an easy trap to fall into.
Assuming equality of floating point numbers computed by two different
paths is always a trap.
R doesn't try to obtain results that are equal to the last bit in other
circumstances; why should it do so here? For example, one somewhat
controversial choice in R is to use 64 bit precision in intermediate
computations when available, rather than rounding everything to 52 bits
as it does when stored to memory in doubles. This means that the value
you get is likely to be closer to the truth than if you did the rounding
earlier, but it is also subject to change according to optimization
level, compiler version, etc.
Duncan Murdoch
-s
On Wed, Feb 18, 2009 at 11:39 AM, Martin Maechler
<maech...@stat.math.ethz.ch> wrote:
"SM" == Stavros Macrakis <macra...@alum.mit.edu>
on Wed, 18 Feb 2009 10:00:40 -0500 writes:
SM> Nice! Glad to hear it. It sounds as though it is still possible for
SM> cumsum(x)[length(x)] to not be exactly equal to sum, though?
Well, possible, probably yes, platform-dependently;
However I vaguely remember that I didn't see one such case in the few
experiments I did.
Martin
SM> On Wed, Feb 18, 2009 at 8:03 AM, Martin Maechler
SM> <maech...@stat.math.ethz.ch> wrote:
SM> ...
>> o cumsum(x) and cumprod(x) for double precision x now use a long
>> double accumulator where available and so more closely match
>> sum() and prod() in potentially being more accurate.
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