Yule-Walker Estimation for the Moving-Average Model | Zendy

Chrysoula Dimitriou-Fakalou | Zendy

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Yule-Walker Estimation for the Moving-Average Model

Author(s) -

Chrysoula Dimitriou-Fakalou

Publication year - 2011

Publication title -

international journal of stochastic analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.19

H-Index - 28

eISSN - 2090-3340

pISSN - 2090-3332

DOI - 10.1155/2011/151823

Subject(s) - mathematics , estimator , gaussian , generalized method of moments , estimation , matrix (chemical analysis) , autoregressive model , variance (accounting) , statistics , set (abstract data type) , computer science , physics , materials science , management , accounting , business , quantum mechanics , economics , composite material , programming language

The standard Yule-Walker equations, as they are known for an autoregression, are generalizedto involve the moments of a moving-average process indexed on any number of dimensions. Onceobservations 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

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