Validity of Edgeworth expansions of minimum contrast estimators for Gaussian ARMA processes

Masanobu Taniguchi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Let {Xt} be a Gaussian ARMA process with spectral density fθ(λ), where θ is an unknown parameter. To estimate θ we propose a minimum contrast estimation method which includes the maximum likelihood method and the quasi-maximum likelihood method as special cases. Let θ̂τ be the minimum contrast estimator of θ. Then we derive the Edgewroth expansion of the distribution of θ̂τ up to third order, and prove its valldity. By this Edgeworth expansion we can see that this minimum contrast estimator is always second-order asymptotically efficient in the class of second-order asymptotically median unbiased estimators. Also the third-order asymptotic comparisons among minimum contrast estimators will be discussed.

Original languageEnglish
Pages (from-to)1-28
Number of pages28
JournalJournal of Multivariate Analysis
Issue number1
Publication statusPublished - 1987 Feb
Externally publishedYes


  • Edgeworth expansion
  • Gaussian ARMA processes
  • maximum likelihood estimator
  • minimum contrast estimator

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty


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