On Fri, Sep 30, 2011 at 5:43 AM, Jan Wijffels <jwijff...@bnosac.be> wrote: > Hi R-helpers > > I'm looking for a vectorised function which does missing value replacement > as in last observation carried forward in the zoo package but instead of a > locf, I would like the locf function to add +1 to each time a missing value > occurred. See below for an example. > >> require(zoo) >> x <- 5:15 >> x[4:7] <- NA >> coredata(na.locf(zoo(x))) > [1] 5 6 7 7 7 7 7 12 13 14 15 > But what I need is > 5 6 7 7+1 7+1+1 7+1+1+1 7+1+1+1+1 12 13 14 15 > to obtain > [1] 5 6 7 8 9 10 11 12 13 14 15 > I could program this in C but if anyone has already done this I would be > interested in seeing their vectorized solution. >
Try this (where x is from the question): > ix <- cumsum(is.na(x)) > na.locf(x) + ix - cummax(ix * !is.na(x)) [1] 5 6 7 8 9 10 11 12 13 14 15 Because of the way x was constructed in this test case the result is actually the same as linear interpolation (though not in general) so if that were what is wanted then it would just be: > na.approx(x) [1] 5 6 7 8 9 10 11 12 13 14 15 -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.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.
