Improved estimation for the autocovariances of a Gaussian stationary process

Masanobu Taniguchi, Hiroshi Shiraishi, Hiroaki Ogata

研究成果: Article査読

1 被引用数 (Scopus)

抄録

For a Gaussian stationary process with mean μ and autocovariance function λ(̇), we consider to improve the usual sample autocovariances with respect to the mean squares error (MSE) loss. For the cases μ=0 and μ ≠0, we propose sort of empirical Bayes type estimators γ̂ and γ̃, respectively. Then their MSE improvements upon the usual sample autocovariances are evaluated in terms of the spectral density of the process. Concrete examples for them are provided. We observe that if the process is near to a unit root process the improvement becomes quite large. Thus, consideration for estimators of this type seems important in many fields, e.g., econometrics.

本文言語English
ページ(範囲)269-277
ページ数9
ジャーナルStatistics
41
4
DOI
出版ステータスPublished - 2007 8月 1
外部発表はい

ASJC Scopus subject areas

  • 統計学および確率
  • 統計学、確率および不確実性

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