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Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

An orthogonality-based estimation of moments for linear mixed models

Language

English

Abstract

Estimating higher-order moments, particularly fourth-order moments in linear mixed models is an important, but difficult issue. In this article, an orthogonality-based estimation of moments is proposed. Under only moment conditions, this method can easily be used to estimate the model parameters and moments, particularly those of higher order than the second order, and in the estimators the random effects and errors do not affect each other. The asymptotic normality of all the estimators is provided. Moreover, the method is readily extended to handle non-linear, semiparametric and non-linear models. A simulation study is carried out to examine the performance of the new method. © 2010 Board of the Foundation of the Scandinavian Journal of Statistics.

Keywords

Asymptotic normality, Linear mixed models, Moment estimator, QR decomposition

Publication Date

2010

Source Publication Title

Scandinavian Journal of Statistics

Volume

37

Issue

2

Start Page

253

End Page

263

Publisher

Wiley

ISSN (print)

03036898

ISSN (electronic)

14679469

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