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Generalized Least Squares Estimation Of Arma Models

Author

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  • L. KAVALIERIS
  • E. J. HANNAN
  • M. SALAU

Abstract

. Two multistage methods for estimating scalar ARMA models are investigated. Both estimate innovations using an autoregression; these are used to obtain initial ARMA parameter estimates by regression and finally the initial estimates are refined by generalized least squares or nonlinear optimization to achieve efficiency. We provide a proof of the generalized least squares procedure.

Suggested Citation

  • L. Kavalieris & E. J. Hannan & M. Salau, 2003. "Generalized Least Squares Estimation Of Arma Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 165-172, March.
  • Handle: RePEc:bla:jtsera:v:24:y:2003:i:2:p:165-172
    DOI: 10.1111/1467-9892.00301
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    Cited by:

    1. Christian Kascha, 2012. "A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models," Econometric Reviews, Taylor & Francis Journals, vol. 31(3), pages 297-324.
    2. Jean-Marie Dufour & Tarek Jouini, 2011. "Asymptotic Distributions for Some Quasi-Efficient Estimators in Echelon VARMA Models," CIRANO Working Papers 2011s-25, CIRANO.
    3. Xinping Xiao & Xue Li, 2023. "A novel compositional data model for predicting the energy consumption structures of Europe, Japan, and China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 11673-11698, October.

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