thanks, mark. these are excellent starting pointers. I will get to them
asap. I hope I won't need to bother you more.
regards,
/iaw
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Hi: see andrew harvey's books for the detailed discussion. His earlier one
( I forget the
title names ) is more comprehensive. But I bet they both talk about it.
what you have is an "almost" random walk with noise model but the
coefficient on the ar(term) is not 1. you can estimate that using the
dear R and stats wizards: I would like to estimate an AR1 model with
constant and measurement noise:
true[t] = a + b*true[t-1] + noise1[t]
observed[t] = true[t] + noise2[t]
(true is never observed.) I am very interested in forecasting
observed[t+1]., and modestly interested in inferring b a
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