Iterative estimating equations: Linear convergence and asymptotic properties

• 成果类型: Article
• 署名作者: Jiang, Jiming; Luan, Yihui; Wang, You-Gan
• 署名单位: University of California System; University of California Davis; Shandong University; Commonwealth Scientific & Industrial Research Organisation (CSIRO)
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053607000000208
• 发表日期: 2007
• 页码: 2233-2260
• 关键词: maximum-likelihood estimation; models

摘要

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.