Bernoulli

  • Bernoulli
  • Volume 18, Number 1 (2012), 206-228.

Efficient estimation of moments in linear mixed models

Ping Wu, Winfried Stute, and Li-Xing Zhu

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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.

Article information

Source
Bernoulli, Volume 18, Number 1 (2012), 206-228.

Dates
First available in Project Euclid: 20 January 2012

Permanent link to this document
https://projecteuclid.org/euclid.bj/1327068623

Digital Object Identifier
doi:10.3150/10-BEJ330

Mathematical Reviews number (MathSciNet)
MR2888704

Zentralblatt MATH identifier
1235.62085

Keywords
asymptotic normality linear mixed model moment estimator

Citation

Wu, Ping; Stute, Winfried; Zhu, Li-Xing. Efficient estimation of moments in linear mixed models. Bernoulli 18 (2012), no. 1, 206--228. doi:10.3150/10-BEJ330. https://projecteuclid.org/euclid.bj/1327068623


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