library (zoo) ?na.approx Note that you need to define an index (time base) to go along with your data, but that could be as simple as a sequence of integers. --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<jdnew...@dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --------------------------------------------------------------------------- Sent from my phone. Please excuse my brevity.
sagarnikam123 <sagarnikam...@gmail.com> wrote: >i have time series as >1.3578511 >0.5119648 >1.3189847 >0.9214787 >1.2272616 >4.9167998 >1.2272616 >1.2272616 >0.8854192 >2.3386331 >1.6132899 >0.2030302 >0.8426226 >1.2277843 >NA >1.3189847 >1.3578511 >0.8530141 >2.3386331 >1.0541099 >0.7747481 >0.5764672 >1.3189847 >1.2160533 >1.2272616 >0.6715839 >0.9651803 >1.6132899 >1.2006974 >0.6875047 >1.3245534 >1.2006974 >0.8221709 >1.3101684 >1.6132899 >1.6132899 >1.2006974 >1.3189847 >1.0018480 >1.2277843 >1.4424190 >1.6132899 >1.2277843 >1.2006974 >0.7779642 >0.9381081 >0.8854192 >NA >NA >1.3189847 >1.1070461 >0.8221709 >4.9167998 >0.9214787 >1.3189847 >1.3189847 >1.2277843 >1.4424190 >1.6132899 >1.6132899 >4.9167998 >0.8235792 >0.9708839 >1.1070461 >1.2160533 >0.8354292 >1.4424190 >1.1958634 >0.5119648 >1.4424190 >1.4424190 >1.6132899 >1.6132899 >0.6710844 >1.2272616 >0.9708839 >0.8890464 >1.4424190 >0.8890464 >0.8221709 >1.1958634 >0.8132233 >0.4630722 >4.9167998 >0.8890464 >1.3189847 >0.7373181 >1.1070461 >1.2279813 >0.8890464 >0.3588158 >1.4424190 >0.8132233 >0.4297043 >1.3578511 >4.9167998 >1.2272616 >0.8426226 >1.4424190 >1.6132899 >NA > > >in which NA are missing values,i want to predict/forecast it,i search >on >internet,i found that Amelia packages can impute missing values; >i used but it giving error,how can i resolve it > >library(Amelia) >t<-read.table("C:\\Users\\exam\\Desktop\\missing_ts.txt") > >> a.out <- amelia(t) >Amelia Error Code: 42 >There is only 1 column of data. Cannot impute > >> amelia(x=as.matrix(1:101,t$V1)) >Amelia Error Code: 39 >Your data has no missing values. Make sure the code for >missing data is set to the code for R, which is NA > >> amelia(t$V1) >Error in colSums(!is.na(x)) : > 'x' must be an array of at least two dimensions > >is my way of predicting wrong?,if yes,then which method should i >follow? > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >-- >View this message in context: >http://r.789695.n4.nabble.com/how-to-predict-forecast-missing-values-in-time-series-tp4630588.html >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. ______________________________________________ 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.