[R] slowness of auto.arima() from package forecast (was Execution time very high in linux)

[Prof Brian Ripley]

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,                  ripley at stats.ox.ac.uk
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)
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