Dear users, I am struggling with this issue. I want to estimate a VAR(1) for three variables, say beta1 beta2 beta3, using monthly observations from January 1984 to September 2009. In-sample period January 1984 to December 2003, out-of-sample January 2004 to September 2009. This is what I have done at the moment betas<-read.table("C:\\Users\\Manta\\Desktop\\betas.txt",header=T,dec=",") BETA<-ts(betas,start=(1984),frequency=12) BETAS<-TSdata(output=BETA) VAR1<-estVARXls(window(BETAS,end=c(2003,12)),max.lag=1) pr<-forecast(VAR1,horizon=1) pr3<-forecast(VAR1,horizon=3) pr12<-forecast(VAR1,horizon=12) and the model is estimated correctly (same estimates as found using other softwares) Then the tricky part: I want to estimate the betas for January 2004, March 2004 and January 2005 (that is, 1-3-12 months horizon). BUT, when estimating March 2004, I just want March 2004, and not also again January 2004 and February 2004. Same thing for January 2005. I tried to use the function horizonForecasts but it seems not working properly. Then, I want to compare the forecasts with the actual betas in order to get RMSE and MAE. So I tried the following: betas[241,]-pr$forecast error BETA[241,]-pr$forecast non-numeric argument to binary operator BETAS[241,]-pr$forecast incorrect number of dimensions So, I do not know how to solve this. This computation then needs to be put in a loop, with expanding (or rolling, that's not a big issue), so then I will compare betas forecasts for February 2004 (April 2004 and February 2005) with the actual data and so on. Thanks in advance! -- View this message in context: http://old.nabble.com/VAR-forecasts-and-out-of-sample-prediction-tp26540692p26540692.html Sent from the R help mailing list archive at Nabble.com.