Thanks Gabor!!

On 1/6/08, Gabor Grothendieck <ggrothendieck@gmail.com> wrote:
>
> On Jan 6, 2008 5:17 PM, tom soyer <tom.soyer@gmail.com> 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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