Estimation of Sampling (Co)variances of the REML Estimators for Variance Components in a Mixed Linear Model.

DOI 13 References Open Access
  • Ashida Ichiro
    Department of Animal Science, Faculty of Agriculture, Niigata University
  • Iwaisaki Hiroaki
    Department of Animal Science, Faculty of Agriculture, Niigata University

Bibliographic Information

Other Title
  • 混合線形モデルにおける分散成分の最尤推定量の抽出（共）分散の推定

Description

We derive an expression of sampling (co) variances of the restricted maximum likelihood estimators of variance components in a mixed linear model with one random effect except for the residual term. The given matrix describing the sampling (co) variances is not a log likelihood-based one, but is rather developed noticing the equivalence between the restricted maximum likelihood estimators and the corresponding estimators by a minimum variance quadratic unbiased estimation in which the prior information for the variance ratio is based on the restricted maximum likelihood estimators of variance components. The current approach takes account of the exact (co) variances of the quadratics for the minimum variance quadratic unbiased estimation under normality, and the matrix derived is different from the inverse of the so-called information matrix which represents the large-sample, asymptotic dispersion matrix of the restricted maximum likelihood estimators. A numerical comparison is conducted to confirm the validity of our approach.

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Details 詳細情報について

  • CRID
    1390282679347008256
  • NII Article ID
    130002152021
  • DOI
    10.5691/jjb.16.9
  • ISSN
    21856494
    09184430
  • Text Lang
    en
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
    • OpenAIRE
  • Abstract License Flag
    Disallowed

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