Hello,
I have a similar problem but in my case I have a seasonal time series and the gaps are bigger. Like I said the TS as a seasonality to the week and some gaps are so big that seasonality is broken. I need a process to predict this values and keep the seasonality. From the search that I made I don't found any process to do this. Any ideas are welcome! Thanks in advance, João Santos Horace Tso wrote: > > Erik, indeed it gets the work done. I was hoping to avoid the dreaded > looping, though..... > > Thanks. > > Horace > >>>> Erik Iverson <[EMAIL PROTECTED]> 6/22/2007 12:01 PM >>> > I think my example should work for you, but I couldn't think of a way to > do this without an interative while loop. > > test <- c(1,2,3,NA,4,NA,NA,5,NA,6,7,NA) > > while(any(is.na(test))) > test[is.na(test)] <- test[which(is.na(test))-1] > > test > [1] 1 2 3 3 4 4 4 5 5 6 7 7 > > Horace Tso wrote: >> Folks, >> >> This must be a rather common problem with real life time series data >> but I don't see anything in the archive about how to deal with it. I >> have a time series of natural gas prices by flow date. Since gas is not >> traded on weekends and holidays, I have a lot of missing values, >> >> FDate Price >> 11/1/2006 6.28 >> 11/2/2006 6.58 >> 11/3/2006 6.586 >> 11/4/2006 6.716 >> 11/5/2006 NA >> 11/6/2006 NA >> 11/7/2006 6.262 >> 11/8/2006 6.27 >> 11/9/2006 6.696 >> 11/10/2006 6.729 >> 11/11/2006 6.487 >> 11/12/2006 NA >> 11/13/2006 NA >> 11/14/2006 6.725 >> 11/15/2006 6.844 >> 11/16/2006 6.907 >> >> What I would like to do is to fill the NAs with the price from the >> previous date * gas used during holidays is purchased from the week >> before. Though real simple, I wonder if there is a function to perform >> this task. Some of the imputation functions I'm aware of (eg. impute, >> transcan in Hmisc) seem to deal with completely different problems. >> >> 2.5.0/Windows XP >> >> Thanks in advance. >> >> HT >> >> ______________________________________________ >> [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. > > ______________________________________________ > [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. > > -- View this message in context: http://www.nabble.com/Imputing-missing-values-in-time-series-tf3966333.html#a13632881 Sent from the R help mailing list archive at Nabble.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.
