On Jan 6, 2008 5:17 PM, tom soyer <
[hidden email]> wrote:
> Hi,
>
> I have a ts object with a frequency of 4, i.e., quarterly data, and I would
> like to calculate the mean for each quarter. So for example:
>
> > ts.data=ts(1:20,start=c(1984,2),frequency=4)
> > ts.data
> Qtr1 Qtr2 Qtr3 Qtr4
> 1984 1 2 3
> 1985 4 5 6 7
> 1986 8 9 10 11
> 1987 12 13 14 15
> 1988 16 17 18 19
> 1989 20
>
> If I do this manually, the mean for the 1st quarter would be
> mean(c(4,8,12,16,20)), which is 12. But I am wondering if there is a R
> function that could do this faster. I tried aggregate.ts but it didn't work:
>
> > aggregate(ts.data,nfrequency=4,mean)
> Qtr1 Qtr2 Qtr3 Qtr4
> 1984 1 2 3
> 1985 4 5 6 7
> 1986 8 9 10 11
> 1987 12 13 14 15
> 1988 16 17 18 19
> 1989 20
>
> Does anyone know what am I doing wrong?
aggregate.ts aggregates to produce series of coarser granularity
which is not what you want. You want the ordinary aggregate:
aggregate(c(ts.data), list(qtr = cycle(ts.data)), mean)
# or tapply:
tapply(ts.data, cycle(ts.data), mean)
See ?aggregate
______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide
http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
Locked
