Colleagues I am a new to R but already love it.
I have the following problem: I fitted arima model to my time series like this (please ignore modeling parameters as they are not important now): x = scan("C:/data.txt") x = ts(x, start=1, frequency=1) x.fit<-arima(x, order = c(1,0,0), seasonal = list(order=c(0,0,1))) Now I want to use this model for forecasting and backtesting (!). My goal is to apply exactly this model to different data – another time series object, let’s call it “y”. How can I do this in R. One of the options is to extract coefficients and to create my own function that can be applied to any time series but I suspect and hope that there is a better way of doing this. If there is not an easy option can anyone suggest a complete equation that includes seasonal terms that can be easily programmed (for example in C) for a person who knows some programming but very little math. Thank you. -- View this message in context: http://r.789695.n4.nabble.com/Manually-reconstructing-arima-model-from-coefficients-tp4566082p4566082.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.