Two-step residual-based estimation of error variances for generalized least squares in split-plot experiments

研究成果: Article査読

抄録

In split-plot experiments, estimation of unknown parameters by generalized least squares (GLS), as opposed to ordinary least squares (OLS), is required, owing to the existence of whole- and subplot errors. However, estimating the error variances is often necessary for GLS. Restricted maximum likelihood (REML) is an established method for estimating the error variances, and its benefits have been highlighted in many previous studies. This article proposes a new two-step residual-based approach for estimating error variances. Results of numerical simulations indicate that the proposed method performs sufficiently well to be considered as a suitable alternative to REML.

本文言語English
ページ(範囲)342-358
ページ数17
ジャーナルCommunications in Statistics: Simulation and Computation
43
2
DOI
出版ステータスPublished - 2014 1 1

ASJC Scopus subject areas

  • 統計学および確率
  • モデリングとシミュレーション

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