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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Year of publication:	1991
Authors:	Breid, F. Jay ; Davis, Richard A. ; Lh, Keh-Shin ; Rosenblatt, Murray
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 36.1991, 2, p. 175-198
Publisher:	Elsevier
Keywords:	maximum likelihood estimates asymptotic normality autoregressive process nonminimum phase noncausal

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005221612