From: Rolf Turner <rolf_at_math.unb.ca>

Date: Fri 02 Jul 2004 - 23:46:36 EST

.

Coefficients:

R-help@stat.math.ethz.ch mailing list

https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Jul 02 23:50:15 2004

Date: Fri 02 Jul 2004 - 23:46:36 EST

The seasonal aspect of arima models allows, essentially, for a
special realtionship between X_t and X_{t+s} where s is the
``seasonality'' of the model. It (``the model'') couldn't care less
what the time ***units*** are --- they could be weeks, quarters,
days, hours, microseconds, 1.14135*microseconds, .... What matters
is: Do you have reason to believe that there is a special
relationship between X_t and X_{t+s}??? If so, go for it. If not,
don't.

Such relationships are ***most likely*** to arise in quarterly and monthly data --- with s = 4 in the quarterly data, s = 12 in the monthly data. You could conceiveably get seasonality with s = 7 in daily data; at a stretch with s = 30 (pretending all months are 30 days long ... a bit dubious). You might (ah, well, sort of ....) also have s = 365 seasonality in daily data, but such a large s is unlikely to ``work'' very well. You might get seasonality with s = 52 in weekly data. (Dubious.) You might get seasonality with s = 24 in hourly data. U.s.w.

===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===

> set.seed(42) > x <- arima.sim(list(ar=c(0,0,0,0.5)),300) > f1 <- arima(x,seasonal=list(order=c(1,0,0),period=4)) > f2 <- arima(x,order=c(4,0,0),fixed=c(0,0,0,NA,NA),transform.pars=FALSE) > f1

.

Coefficients:

sar1 intercept 0.4987 -0.0775 s.e. 0.0499 0.1051

sigma^2 estimated as 0.8536: log likelihood = -402.51, aic = 811.02

> f2

.

Coefficients:

ar1 ar2 ar3 ar4 intercept 0 0 0 0.4987 -0.0774 s.e. 0 0 0 0.0499 0.1051

sigma^2 estimated as 0.8536: log likelihood = -402.51, aic = 811.02 ===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===

Hope this is a bit enlightening.

cheers,

Rolf Turner rolf@math.unb.ca

> Hello R People:

*>
**> When using the arima function with the seasonal option, are the
**> seasonal options only good for monthly and quarterly data, please?
**>
**> Also, I believe that weekly and daily data are not appropriate for
**> seasonal parm estimation via arima.
**>
**> Is that correct, please?
**>
**> Thanks,
**> Sincerely,
**> Laura Holt
**> mailto: lauraholt_983@hotmail.com
*

R-help@stat.math.ethz.ch mailing list

https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Jul 02 23:50:15 2004

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