Hi all, I've got an xts time series with monthly OHLC Dow Jones industrial index data from 1980 to present, the data is in stored in x.
I've done an OLS fit on the data in 1982::1994 and stored it in extrapolate1 (x[,4] contains the closing value for the index). > t3 <- seq(1980,1994,length = length(x["1980::1994",4])) > t4<-t3^2 > extrapolate1 <- lines(lm(x["1980::1994",4]~t3+t4)$fit) > extrapolate1 Call: lm(formula = x["1980::1994", 4] ~ t3 + t4) Coefficients: (Intercept) t3 t4 3.161e+07 -3.205e+04 8.125e+00 The plot comes up with the appropriate line fit for 1980::1994, so I can safely say the model/fit is correct. I want to plot the predicted response of extrapolate into 1995 and beyond and after much googling have got about this close -- > new.t <- seq(1995,len=2*12,by = 1/12) > new.dat <- data.frame(Time = new.t, Seas = rep(1:12,2)) > predict(extrapolate1,new.dat)[1:24] 1 2 3 4 5 6 7 8 704.9639 714.5726 724.2807 734.0882 743.9951 754.0014 764.1071 774.3122 9 10 11 12 13 14 15 16 784.6168 795.0207 805.5240 816.1267 826.8288 837.6303 848.5312 859.5315 17 18 19 20 21 22 23 24 870.6313 881.8304 893.1289 904.5268 916.0241 927.6209 939.3170 951.1125 Warning message: 'newdata' had 24 rows but variable(s) found have 180 rows This is straight from the net, the trouble is with how new.dat is set up but I can't figure it out... Regards, Nick [[alternative HTML version deleted]] ______________________________________________ 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.