On Fri, 1 Sep 2017, Andrea Altomani wrote:
I should have formulated my question in a more specific way.
1. I suspect this is a floating point precision issue. I am not very
knowledgeable about R internals, can someone else confirm it?
Yes. If you represent a series with increment 1/12 it depends on how you
do it. As a simple example consider the following two descriptions of the
same time point:
2 - 1/12
## [1] 1.916667
1 + 11/12
## [1] 1.916667
However, both are not identical:
(2 - 1/12) == (1 + 11/12)
## [1] FALSE
The difference is just the .Machine$double.eps:
(2 - 1/12) - (1 + 11/12)
## [1] 2.220446e-16
2. Should this be considered a bug or not, because it is "just a
precision issue"? Should I report it?
I don't think it is a bug because of the (non-standard) way how you
created the time series.
3. How can it happen? From a quick review of ts.R, it looks like the values
of the time index are never modified, but only possibly removed. In my case:
- x and y have the same index.
- the subtraction operator recognizes this, and create a new ts with one
entry
- the result of the subtraction has an index which is different from the
input.
This is very surprising to me, and I am curious to understand the problem.
The object 'x' and hence the object 'y' have the same time index. But in
'z' a new time index is created which is subtly different from that of
'x'. The reason for this is that R doesn't expect an object like 'x' to
exist.
You should create a "ts" object with ts(), e.g.,
x <- ts(2017, start = c(2017, 6), freqency = 12)
But you created something close to the internal representation...but not
close enough:
y <- structure(2017, .Tsp = c(2017.416667, 2017.416667, 12), class = "ts")
The print functions prints both print(x) and print(y) as
Jun
2017 2017
However, aligning the two time indexes in x - y or ts.intersect(x, y) does
not work...because they are not the same
as.numeric(time(x)) - as.numeric(time(y))
## [1] -3.333332e-07
The "ts" code tries to avoid these situations by making many time index
comparisons only up to a precision of getOption("ts.eps") (1e-5 by
default) but this is not used everywhere. See ?options:
'ts.eps': the relative tolerance for certain time series ('ts')
computations. Default '1e-05'.
Of course, you could ask for this being used in more places, e.g., in
stats:::.cbind.ts() where (st > en) is used rather than ((st - en) >
getOption("ts.eps")). But it's probably safer to just use ts() rather than
structure(). Or if you use the latter make sure that you do at a high
enough precision.
hth,
Z
On Fri, Sep 1, 2017 at 5:53 PM Jeff Newmiller <jdnew...@dcn.davis.ca.us>
wrote:
You already know the answer. Why ask?
--
Sent from my phone. Please excuse my brevity.
On September 1, 2017 7:23:24 AM PDT, Andrea Altomani <
altomani.and...@gmail.com> wrote:
I have a time series x, and two other series obtained from it:
x <- structure(2017, .Tsp = c(2017.41666666667, 2017.41666666667, 12),
class = "ts")
y <- floor(x)
z <- x-y
I would expect the three series to have exactly the same index.
However I get the following
time(x)-time(y)
Jun
2017 0
as expected, but
time(x)-time(z)
integer(0)
Warning message:
In .cbind.ts(list(e1, e2), c(deparse(substitute(e1))[1L],
deparse(substitute(e2))[1L]), :
non-intersecting series
and indeed, comparing the indices gives:
time(x)[1]-time(z)[1]
[1] 3.183231e-12
Is this a bug in R, or is it one of the expected precision errors due
to the use of limited precision floats?
I am using R 3.4.0 (2017-04-21) on Windows (64-bit).
Thaks!
Andrea Altomani
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