Thanks Gabor!!
On 1/6/08, Gabor Grothendieck <[EMAIL PROTECTED]> wrote:
>
> On Jan 6, 2008 5:17 PM, tom soyer <[EMAIL PROTECTED]> 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
>
--
Tom
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