Couldn't find this in the archives. I'm fitting a series of historical weather-related data, but would like to use the latest values to forecast. So let's say that I'm using 1970-2000 to fit a model (using fourier terms and arima/auto.arima), but now would like to use the last X values to predict tomorrow's weather. I'm at a loss. All the functions I've come across (like forecast()) use the series and then forecast from the end point.
Do I need to decompose the fit and write it out the long way? For example, Tomorrow = fit$coef[1]*Yesterday + fit$coef[2]*BeforeYesterday + etc or is there a function that I'm not finding? Thank you, Nicole -- View this message in context: http://r.789695.n4.nabble.com/forecasting-a-time-series-tp4308147p4308147.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.
