hi, using articial data, i'm supposed to estimate model
y(t) = beta(1) + beta(2)*x(t) + u(t), u(t) = gamma*u(t-1) + v(t), t = 1,...,100 which is correctly specified in two ways: ML ommiting the first observation, and ML using all 100 observation. since i'm still learning how to use R, i would like to know how MLE works. there is neither information about the distribution of v(t) nor if u(t) follows a stationary process. suppose that v(t) is normaly distributed - so we want to estimate beta(1), beta(2) and sigma2 (the variance of v(t)). thanks in advance! alexandre bonnet getulio vargas foundation, brazil [[alternative HTML version deleted]] ______________________________________________ R-help@stat.math.ethz.ch 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.