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
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