This is not the address of the package maintainer (nor of the person
who wrote to you), nor is that a reproducible example (we don't have
my_file.dat). Please DO study the posting guide!
On Fri, 9 Nov 2007, Joao Santos wrote:
Hello,
EXAMPLE
##Create time series
bb_500 = scan("my_file.dat")
ts <- ts(bb_500, frequency=168)
...
Prof Brian Ripley wrote:
This is not about slowness of Linux nor of R but of a particular function
in a contributed package. Few of us are familiar with that package, and
you have not given a reproducible example. Please do as the posting guide
asked and talk directly to the maintainer (who may well not read this
list).
I've altered the subject line to something less inappropriate.
On Fri, 9 Nov 2007, Joao Santos wrote:
Hello All,
Sorry everybody for another message on this topic but I don't understand
the
times off execution that I have.
From my search in the forum I found that linux old be better to this
kind of
operation, so now I using a dualCore 2.33GHz with 8Gb RAM but the times
off
execution don´t decrease.
Once again the function and the times and I get in linux:
system.time(fit_2323v_168f<-auto.arima(regts.ts, d = NA, D = NA, max.p =
2,
max.q = 2,
max.P = 1, max.Q = 1, max.order = 5,
start.p=0, start.q=0, start.P=0, start.Q=0,
stationary = FALSE, ic = c("aic","aicc", "bic"),
stepwise=FALSE, trace=TRUE))
user system elapsed
38389.75 3786.29 22849.73
There is some optimization that could be done?
Thanks in advance for the replies!!!
João Santos
Joao Santos wrote:
Hello again,
Sorry but the code that I insert wasn't write. Should be like this:
fit_2323v_168f<-auto.arima(regts.ts, d = NA, D = NA, max.p = 2, max.q =
2,
max.P = 1, max.Q = 1, max.order = 5,
start.p=0, start.q=0, start.P=0, start.Q=0,
stationary = FALSE, ic = c("aic","aicc", "bic"),
stepwise=TRUE, trace=TRUE)
Sorry for the SPAM!!
João Santos
Joao Santos wrote:
Hello,
I using the fuction auto.arima() from package forecast to predict the
values of p,d,q and P,D,Q.
My problem is the execution time of this function, for example, a time
series with 2323 values with seasonality to the week take over 8 hours
to
execute all the possibilities.
I using a computer with Windows XP, a processor Intel Core2 Duo T7300
and 2Gb of RAM.
fit_2323v_168f<-auto.arima(regts.ts, d = 1, D = 1, max.p = 2, max.q =
2,
max.P = 1, max.Q = 1, max.order = 5,
start.p=0, start.q=0, start.P=0, start.Q=0,
stationary = FALSE, ic = c("aic","aicc",
"bic"),
stepwise=TRUE, trace=TRUE)
It is any configuration to speed-up this?
Thanks in advance!
João Santos
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
