Couldn't you use seq.Date() to set up the time index and then just fill as
appropriate?
Alternatively, to.weekly if you are starting with a daily series.
Michael
On Nov 22, 2011, at 4:00 PM, "Kevin Burton" <rkevinbur...@charter.net> wrote:
> I was wondering what the best approach is for missing data in a time series.
> I give an example using xts but I would like to know what seems to be the
> "best" method. Say I have
>
>
>
> library(xts)
>
> xts.ts <- xts(1:4,as.Date(c("1970-01-01", "1970-1-3", "1980-10-10",
> "2007-8-19")), frequency=52)
>
>
>
> I would like to turn this into a time series (still could be xts, or
> converted to ts) that has values for every week starting with the week that
> includes the start date and ending with the week that includes the end date.
> If there is data for the week then use it otherwise set it to NA or 0.
> Remember some years have 52, 53, or rarely 54 full or partial weeks. What to
> do with the partials at the beginning and ending of the year? This seems to
> be a fairly common problem and doing it myself is very cumbersome. Does a
> solution to this kind of problem exist? Once the approach to a weekly period
> is found I am sure that adjustment to daily, monthly, or quarterly would be
> relatively straightforward.
>
>
>
> Thank you.
>
>
>
> Kevin
>
>
>
>
> [[alternative HTML version deleted]]
>
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