Hi all, I am running into a problem using forecast with ARIMA models, hope you can help shed some light onto this.
I am fitting several ARIMA models using the auto.arima() function onto several time series, which are basically the residuals from a linear model fit. There are 40 such data points in every series. Lets say for example that auto.arima() returns a ARIMA(0,0,1) model called huc.arima I then try to forecast the points for the next 20 time steps by doing the following: e_t.pred<-forecast(huc.arima,h=length(time.test)) where time.test = 20. However, instead of getting 20 points I am getting only the first point with a non-zero value and 19 other points with value 0. I run into this problem with almost every other time series I try, regardless of the type of ARIMA model. I am thinking it must be something with the way I define the time series data? I am simply taking a vector of numbers and converting to a time series using the ts() function. Any help is much appreciated, thanks! -- View this message in context: http://r.789695.n4.nabble.com/arima-forecasting-problem-tp4636985.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.
