Hi guys, I am afraid I am stuck with an estimation problem.
I have two variables, X and Y. Y is explained by the weighted sum of n lagged values of X. My aim is to estimate the two parameters c(alpha0,alpha1) in: Yt = Sum from j=1 to n of ( ( alpha0 + alpha1 * j ) * Xt-j ) Where Xt-j denotes the jth lag of X. I came up with this approach because I thought it would be a good idea to estimate the slope of the weights rather than estimating one parameter for each lag of X added (I intent to set n very large). Is that easily doable in R? My first try looks like this: parameters<-function(alpha,y){ logl<- for(i in 1:n){ sum((alpha[1]+alpha[2]*i)*lag(xvar,i)) } return(-logl) } optim(c(0.001,0.001),parameters,y=yvar) It is really hard to find any clear sources when it comes to optimization including lags. I would really appreciate if someone could help me out on this one! Kind regards & Happy Easter, Christian [[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.