Hello,
This is FAQ 7.31 Why doesn't R think these numbers are equal?
As for your second question whether this behavior is desirable I think
so, we should be aware that floating-point arithmetics has limits. In
your case, a precision limit. At an R pompt run the instructions
?.Machine
.Machine$double.eps
to see the limits, and more.
As for your first question, you can't prevent but you can correct based
on a chosen accuracy.
Your mesurements were made with how many digits? I doubt you have 16
digits of accuracy. It's possible but it's not usual, it's rare. So you
can round your final value using round().
set.seed(4130)
x <- runif(10)
#?scale
(s <- sum( scale(x, scale = FALSE) ))
#?round
round(s, digits = 10) # suppose you can only be sure of 10 digits.
round(s, digits = 15) # still zero
round(s, digits = 16) # precision loss
Hope this helps,
Rui Barradas
Em 24-08-2012 11:48, Frederik Bertling escreveu:
Hi,
I'm doing some easy calculations to normalize some values. This looks like
this:
x=mean(a+b+c+d ...)
a=a-x
b=b-x
c=c-x
d=d-x
...
mean(a+b+c+d ...) ---> Should now be 0!
However, I'm getting results like -2.315223e-18
This is really near to 0 but not very aesthetic.
Can I prevent this? Or is this behaviour desired?
Thank you very much!
Burtan
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