If I understand:
x.new <- cbind('M.Y'=paste(month.abb[x$month], x$Year, sep="-"), x[-3])
aggregate(list(Change=x.new$price),
list("M.Y"=x.new[,"M.Y"], Year=x.new$Year,
Month=x.new$month), FUN=mean)
On 30/03/2008, Richard Saba <[EMAIL PROTECTED]> wrote:
>
> I have weekly time series data with year, month, day, and price variables.
> The input data set for the weekly series takes the following form:
>
> Year month day price
> 1990 8 20 119.1
> 1990 8 27 124.5
> 1990 9 3 124.2
> 1990 9 10 125.2
> 1990 9 17 126.6
> 1990 9 24 127.2
> 1990 10 1 132.1
> 1990 10 8 133.3
> 1990 10 15 133.9
> 1990 10 22 134.5
> 1990 10 29 133.9
> .. ... ... ...
> ... ... .... ....
> 2008 3 3 313.7
> 2008 3 10 320
> 2008 3 17 325.7
> 2008 3 24 322.4
>
>
> I would like to collapse the data into monthly averages to merge with a
> monthly series. The input data set for the monthly series takes the
> following form:
>
> M-Y Year Month Change
> Aug-1990 1990 8 -226.871
> Sep-1990 1990 9 -896.333
> Oct-1990 1990 10 111.419
> Nov-1990 1990 11 -364.2
> Dec-1990 1990 12 -527.645
> Jan-1991 1991 1 -70.935
> Feb-1991 1991 2 231.214
> Mar-1991 1991 3 -239
>
> ... ... ..... .. ....
>
>
> The merged data set should be of class(ts).
> I can perform the conversions outside of R and then import but I would
> rather perform all conversions within R. I have looked through the zoo and
> Rmetrics packages but without success.
>
> Any help will be appreciated.
> Thanks,
>
> Richard Saba
> Department of Economics
> Auburn University
> Email: [EMAIL PROTECTED]
> Phone: 334 844-2922
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
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