Dimitriou-Fakalou, C. (2011) Yule-Walker estimation for the Moving-Average model. International Journal of Stochastic Analysis, 2011 . pp. 1-20. ISSN 2090-3332.
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The standard Yule-Walker equations, as they are known for an autoregression, are generalized to involve the moments of a moving-average process indexed on any number of dimensions. Once observations become available, new moments estimators are set to imitate the theoretical equations. These estimators are not only consistent but also asymptotically normal for any number of indexes. Their variance matrix resembles a standard result from maximum Gaussian likelihood estimation. A simulation study is added to conclude on their efficiency.
|Additional information:||Article ID 151823|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics|
|Depositing User:||Chrysoula Dimitriou Fakalou|
|Date Deposited:||10 Oct 2012 11:47|
|Last Modified:||12 Feb 2013 09:05|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/31478 (The current URI for this page, for reference purposes)|
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