Efficient estimation of moments in linear mixed models

Ping Wu*, Winfried Stute, Lixing ZHU

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

In the linear random effects model, when distributional assumptions such as normality of the error variables cannot be justified, moments may serve as alternatives to describe relevant distributions in neighborhoods of their means. Generally, estimators may be obtained as solutions of estimating equations. It turns out that there may be several equations, each of them leading to consistent estimators, in which case finding the efficient estimator becomes a crucial problem. In this paper, we systematically study estimation of moments of the errors and random effects in linear mixed models.

Original languageEnglish
Pages (from-to)206-228
Number of pages23
JournalBernoulli
Volume18
Issue number1
DOIs
Publication statusPublished - Feb 2012

Scopus Subject Areas

  • Statistics and Probability

User-Defined Keywords

  • Asymptotic normality
  • Linear mixed model
  • Moment estimator

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