Maximum likelihood estimation for noncausal autoregressive processes
We discuss a maximum likelihood procedure for estimating parameters in possibly noncausal autoregressive processes driven by i.i.d. non-Gaussian noise. Under appropriate conditions, estimates of the parameters that are solutions to the likelihood equations exist and are asymptotically normal. The estimation procedure is illustrated with a simulation study for AR(2) processes.
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Volume (Year): 36 (1991)
Issue (Month): 2 (February)
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