Yes, there is an easy way. Create the regular time series you want by
something like
x <- ts(0, start=c(2000,52), end=c(2003,9), frequency=52)
and fill in the time points you have data for by
xYear <- trunc(times(x)); xWeek <- cycle(x)
attach(mydata)
x[(xYear==year) & (xWeek==Week)] <- Count
detach()
Easy!
On Fri, 14 Feb 2003, Schnitzler, Johannes wrote:
> > I have several large data sets with counts per week.
> > (Maximum week per year is 52. Counts from Week 53
> > are added to week 52.)
> >
> > A data set contains for example:
> >
> > Year Week Count
> > 2000 52 2
> > 2001 1 5
> > 2001 2 7
> > 2001 5 4
> > 2001 7 2
> > ... ... ...
> > ... ... ...
> >
> > Weeks with 0 counts are not listed in the data set.
> > I want to perform time series analysis (frequency 52).
> >
> >
> > Is there an easy way to expand the data set to:
> >
> > Year Week Count
> > 2000 52 2
> > 2001 1 5
> > 2001 2 7
> > 2001 3 0
> > 2001 4 0
> > 2001 5 4
> > 2001 6 0
> > 2001 7 2
> > ... ... ...
> > ... ... ...
> >
> > or is there already a function in "ts", which i have not
found so far,
> > to deal with this problem?
> >
> >
> > Thank you very much.
> >
> > Johannes Schnitzler
> > Germany Berlin
> >
> >
> >
>
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>
--
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)
Oxford OX1 3TG, UK Fax: +44 1865 272595