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On uniform asymptotic normality of sequential least squares estimators for the parameters in a stable AR(p)

For a stable autoregressive process of order p with unknown vector parameter [theta], it is shown that under a sequential sampling scheme with the stopping time defined by the trace of the observed Fisher information matrix, the least-squares estimator of [theta] is asymptotically normally distributed uniformly in [theta] belonging to any compact set in the parameter region.
Year of publication:
2004
Authors: Galtchouk, L. ; Konev, V.
Published in:
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 91.2004, 2, p. 119-142
Publisher: Elsevier
Keywords: Autoregressive process Least-squares estimator Sequential estimation Uniform asymptotic normality
Type of publication: Article
Source:
Persistent link: https://www.econbiz.de/10005221431
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