On 4/12/07, tom soyer <[EMAIL PROTECTED]> wrote: > What should I do for weekly and daily data series? Are there functions > similar to yearmon() for other time intervals? I see that there is a > built-in yearqtr() function for quarterly data, but that's it.
ts series cannot directly represent daily and weekly series other than somehow deciding on a numeric representation for time. Here we will use the number of days and the number of weeks since the Epoch (1970-01-01) and assume we assume weeks start on Sunday. We will also do it over again using the number of weeks since the first point in the series and the number of days since the first point. Lines.raw is from my original post on this thread. z <- read.zoo(textConnection(Lines.raw), header = TRUE, sep = ",") # ts series will represent days as no of days since Epoch zday <- z frequency(zday) <- 1 tsday <- as.ts(zday) # ts series will represent weeks as no of weeks since Epoch zweek <- zday offset <- -3 # weeks start on Sun # offset <- -4 # weeks start on Mon zweek <- aggregate(z, (as.numeric(time(z)) + offset) %/% 7, mean) frequency(zweek) <- 1 tsweek <- as.ts(zweek) ########################################################## # alternately use number of days since first day in series # and number of weeks since first week in series zday0 <- aggregate(zday, time(zday) - min(time(zday)), c) frequency(zday0) <- 1 tsday0 <- as.ts(zday0) zweek0 <- aggregate(zweek, time(zweek) - min(time(zweek)), c) frequency(zweek0) <- 1 tsweek0 <- as.ts(zweek0) ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
