Sorry for the basic question - bur I ran into something I haven't
noticed before and would appreciate a little more perspective on my
problem.
I am using R to determine if various thresholds are hit (or surpassed)
in a data set. If a threshold is surpassed, I have had no problems
identifying it. However, when the threshold is matched *exactly*, not
all cases are being identified.
Please consider the following example, with base value of x = 59000
and threshold of 10% - so the target to hit is 59000*1.1 = 64900.
> x <- 59000
> thresh <- 0.10
>
> target <- x*(1+thresh)
> target
[1] 64900
>
>
> target == 64900
[1] FALSE
>
>
> target-64900
[1] 7.275958e-12
Why is there this (very) small difference in the value of target and
the numeric 64900? Is this using a floating point system or something
else that I'm not understanding?
Is using round() the best work-around in cases such as these - or is
there a better (perhaps more accurate) way to classify data in cases
such as this - avoiding whatever floating points are taking place in
the background in the first place?.
I'm using an older version of R if that matters at all...
R.version
_
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major 2
minor 8.1
year 2008
month 12
day 22
svn rev 47281
language R
version.string R version 2.8.1 (2008-12-22)
Thanks in advance,
Brigid
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