Estimating variance of random effects to solve multiple problems simultaneously

研究成果: Contribution to journalArticle査読

5 被引用数 (Scopus)

抄録

The two-level normal hierarchical model (NHM) has played a critical role in statistical theory for the last several decades. In this paper, we propose random effects variance estimator that simultaneously (i) improves on the estimation of the related shrinkage factors, (ii) protects empirical best linear unbiased predictors (EBLUP) [same as empirical Bayes (EB)] of the random effects from the common overshrinkage problem, (iii) avoids complex bias correction in generating strictly positive second-order unbiased mean square error (MSE) (same as integrated Bayes risk) estimator either by the Taylor series or single parametric bootstrap method. The idea of achieving multiple desirable properties in an EBLUP or EB method through a suitably devised random effects variance estimator is the first of its kind and holds promise in providing good inferences for random effects under the EBLUP or EB framework. The proposed methodology is also evaluated using a Monte Carlo simulation study and real data analysis.

本文言語英語
ページ(範囲)1721-1741
ページ数21
ジャーナルAnnals of Statistics
46
4
DOI
出版ステータス出版済み - 8 2018
外部発表はい

All Science Journal Classification (ASJC) codes

  • 統計学および確率
  • 統計学、確率および不確実性

フィンガープリント

「Estimating variance of random effects to solve multiple problems simultaneously」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル