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October 2007 Iterative estimating equations: Linear convergence and asymptotic properties
Jiming Jiang, Yihui Luan, You-Gan Wang
Ann. Statist. 35(5): 2233-2260 (October 2007). DOI: 10.1214/009053607000000208

Abstract

We propose an iterative estimating equations procedure for analysis of longitudinal data. We show that, under very mild conditions, the probability that the procedure converges at an exponential rate tends to one as the sample size increases to infinity. Furthermore, we show that the limiting estimator is consistent and asymptotically efficient, as expected. The method applies to semiparametric regression models with unspecified covariances among the observations. In the special case of linear models, the procedure reduces to iterative reweighted least squares. Finite sample performance of the procedure is studied by simulations, and compared with other methods. A numerical example from a medical study is considered to illustrate the application of the method.

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Jiming Jiang. Yihui Luan. You-Gan Wang. "Iterative estimating equations: Linear convergence and asymptotic properties." Ann. Statist. 35 (5) 2233 - 2260, October 2007. https://doi.org/10.1214/009053607000000208

Information

Published: October 2007
First available in Project Euclid: 7 November 2007

zbMATH: 1126.62025
MathSciNet: MR2363970
Digital Object Identifier: 10.1214/009053607000000208

Subjects:
Primary: 62F12 , 62J02 , 65B99

Keywords: Asymptotic efficiency , consistency , iterative algorithm , linear convergence , longitudinal data , semiparametric regression

Rights: Copyright © 2007 Institute of Mathematical Statistics

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Vol.35 • No. 5 • October 2007
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