Hi: I have two time series y(t) and x(t). I want to regress Y on X. Because Y is a time series and may have autocorrelation such as AR(p), so it is not efficient to use OLS directly. The model I am trying to fit is like Y(t)=beta0+beta1*X(t)+rho*Y(t-1)+e(t)
e(t) is iid normal random error. Anybody know whether there is a function in R can fit such models? The function can also let me specify how many beta's and rho's I can have in the model. Thx a lot! liu ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
