Department of Mathematics
Efficient estimation of moments in linear mixed models
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. © 2012 ISI/BS.
Asymptotic normality, Linear mixed model, Moment estimator
Source Publication Title
Bernoulli Society for Mathematical Statistics and Probability
Link to Publisher's Edition
Wu, Ping, Winfried Stute, and Li-Xing Zhu. "Efficient estimation of moments in linear mixed models." Bernoulli 18.1 (2012): 206-228.