Hi Eran, You have already gotten some suggestions from Michael, but I think that Rich is correct to question the rational. Any mechanism you choose to replace the missing values will impose its structure on the data. Veritate ab absurdo:
## data x <- sin(seq(1, 17, .1)) + seq(-.5, .5, length.out = 161) y <- x <- ts(x, start = Sys.Date(), end = Sys.Date() + 160) ## add missing values to y y[-c(1, length(x))] <- NA ## interpolate linearlly y[-length(y)] <- cumsum(c(y[1], rep(diff(y[!is.na(y)])/sum(is.na(y)), sum(is.na(y))))) ## plot dev.new(height = 5, width = 10) par(mfrow= c(1, 2)) plot(y, ylim = range(x)) plot(x, ylim = range(x)) Cheers, Josh On Mon, Sep 12, 2011 at 1:42 AM, Eran Eidinger <e...@taykey.com> wrote: > Hello, > > I have a time-series that has some missing samples. > I was thinking on completing them using either zero-order hold or linear > interpolation. > I am looking for an efiicient way (other than a loop...) of identifiying the > missing time slots and filling them. > > Can you think of any methods that might help here? (obviously > which(diff(time)>min(diff(time))) will give the locations, but what > then....?) > > Thanks, > Eran. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org 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. > -- Joshua Wiley Ph.D. Student, Health Psychology Programmer Analyst II, ATS Statistical Consulting Group University of California, Los Angeles https://joshuawiley.com/ ______________________________________________ R-help@r-project.org 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.
