Hi, I have been using this website ( http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm ) to help me to fit ARIMA models to my data. At the moment I have two possible methods to use.
Method 1 If I use arima(ts.data, order=c(1,2,0), xreg=1:length(ts.data)) then the wrong value for the intercept/mean is given (checked on SPSS and Minitab) and also, this is produced In sqrt(diag(x$var.coef)) : NaNs produced Which means that the t-values (for the coefficients) are NaNs, which in turn means that the p-values are NaNs. Although, using this method gives the correct forecast (using predict) and enables ts.plot to show the forecast and 95% CI's. Method 2 If I use diff(diff(ts.dat)) and then apply an ARIMA(1,0,0) to it, then this gives the correct coefficients but the forecasts are wrong (ie they are flat and do not follow the trend). Could anyone think of a way to get both the coefficients AND the forecasts correct? Thanks. -- View this message in context: http://www.nabble.com/Time-Series---ARIMA-differencing-problem-tp22353903p22353903.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.