aggregate(as.ts(c(1,2,3,4,5,6,7,8,9,10)),1/2,mean)
Time Series:
Start = 1
End = 9
Frequency = 0.5
[1] 1.5 3.5 5.5 7.5 9.5
aggregate(as.ts(c(1,2,3,4,5,6,7,8,9,10)),1/5,mean)
Error in sprintf(gettext(fmt, domain = domain), ...) :
use format %f, %e or %g for numeric objects
I must be
I am working on automatic optimization of ARIMA parameters.
That takes a lot of computing power, which I would like to reduce by aggregating
and smoothing.
Any thoughts on the subject?
Suggested algorithms?
What is the best order? aggregate then smooth or smooth then aggregate?
Many thanks in
Quoting Andrew West [EMAIL PROTECTED]:
Take a look at Hyndman's Forecast package, and dse1 2, and see if that
will do what you need.
Looks extremely interesting, especially the Hyndman package.
Thank you very much indeed.
--
Jean-Luc
__
Is there such a beast implemented in R, something like
http://www.spss.com/trends/?
Many thanks in advance,
--
Jean-Luc
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide!
Quoting tom wright [EMAIL PROTECTED]:
On Mon, 2005-19-09 at 10:36 -0400, tom wright wrote:
I'm not an engineer so I hope I'm using the correct terminology here. I
have a recorded waveform that I want to apply low and high pass filters
too, are tehre already R functions existing to do this
Quoting Tyler Smith [EMAIL PROTECTED]:
Hi,
I'm working on a MEPIS (Debian-based Linux) computer, using the
emacs/ESS package to do my R work. I've got some plots that I label
interactively using the locate function. With the Windows GUI there is
an option to take a snapshot of the graphics
There has been a few questions on the subject lately.
Is there any book on the subject, if possible with a computer processing flavor,
that you would highly recommend?
Many thanks in advance,
--
Jean-Luc
__
R-help@stat.math.ethz.ch mailing list
Quoting Spencer Graves [EMAIL PROTECTED]:
1. Have you read the appropriate chapter in Venables and Ripley
(2002) Modern Applied Statists with S (Springer)? If no, I suggest you
start there.
2. Have you worked through the vignettes associated with the zoo
package? If no,
Hello.
This is my first post, so allow me to introduce myself.
But first, I'd like to thank all the authors and contributors to the R software,
as I think that it is truly a great and very useful package.
I am the author of moodss, a GPL modular monitoring application
