On the asymptotic relative efficiency of gaussian and least squares estimators for vector arma models

D. S. Poskitt, M. O. Salau

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This paper is concerned with the asymptotic relative efficiency of the Gaussian and least squares estimators when employed to estimate the parameters of vector ARMA models presented in echelon canonical form. The relative efficiency is assessed via the variance-covariance matrices of the limiting normal distributions of the two estimators. Situations under which substantial loss or gain in efficiency could be exprected are discussed and illustrated with some numerical examples.

Original languageEnglish
Pages (from-to)294-317
Number of pages24
JournalJournal of Multivariate Analysis
Issue number2
Publication statusPublished - 1 Jan 1994
Externally publishedYes


  • Asymptotic relative efficiency
  • Central limit theorem
  • Echelon canonical form
  • Gaussian estimator
  • Kronecker indices
  • Least squares estimator
  • Vector time series models

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