jim holtman a écrit :

Depending on how you are using POSIXct, you accuracy is limited to the
microsecond level.  It is stored as a floating point number with 54
bit of accuracy (~16 digits) and currently the number of seconds since
1/1/1970 is 10 digits, so with microseconds adding 6 more, you are at
the limit:

x <- Sys.time()
x
[1] "2010-02-06 09:34:58 EST"
unclass(x)
[1] 1265466899
x
[1] "2010-02-06 09:34:58 EST"
y <- x+.000001
x-y
Time difference of -9.536743e-07 secs
y <- x+.0000001
x-y
Time difference of 0 secs
y <- x+.000001  # 1 us
identical(x,y)
[1] FALSE
y <- x+.0000001  # 0.1 us
identical(x,y)
[1] TRUE


On Sat, Feb 6, 2010 at 9:41 AM, Laurent Rhelp <laurentrh...@free.fr> wrote:
Gabor Grothendieck a écrit :

zoo is independent of time and date class so it does not restrict your
choice of index class.  POSIXct supports sub-microsecond accuracy.
See ?POSIXct .  Simply using the number of microseconds since the
start of the experiment is another possibility.

On Sat, Feb 6, 2010 at 8:25 AM, Laurent Rhelp <laurentrh...@free.fr>
wrote:

Dear R-List,

I have the habit of using R for my data processing and I like to use the
power of the lattice package. Presently, I have to manage time series.
So,
in order to work properly I want to discover the zoo package and the
related
methods (since lattice can work with zoo class). But my physical
experiment
lasts only one second and my sampling period is equal to 1 microsecond
(the
date time value is given by the IRIG Card for my data acquisition card).
I
read the R-News june 2004 about the date time Classes in R and there is
no
information about allowing for the microseconds. So do you think it is
really a good idea to try to use the R time series framework (zoo package
for example) with my data ? Or would there be a tip ?

Thank you very much

Laurent

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Thank you, I will see in details the POSIXct class.

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This is a good piece of advice ! Thank you very much, I will take care of it in my calculations.

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