convert weekly time series data to monthly
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 <sabaric at auburn.edu> 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: sabaric at auburn.edu Phone: 334 844-2922
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