Estimation in a semiparametric model for longitudinal data with unspecified dependence structure
Estimation in a semiparametric model for longitudinal data with unspecified dependence structure
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DOI：
10.1093/biomet/89.3.579
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发表时间：
2002-09-01
期刊：
影响因子：
2.7
通讯作者：
Fung, WK
中科院分区：
文献类型：
--
作者：
He, XM;Zhu, ZY;Fung, WK
本文将独立观测半参数模型的M-估计推广到纵向数据的情形。我们近似的非参数函数的回归样条，任何M-估计算法通常的线性模型，然后可以用来获得一致的估计模型和有效的大样本推断的回归参数，而没有任何规格的误差分布和协方差结构。包括作为特殊情况下的条件均值和中位数函数的纵向数据的分析。
This paper considers an extension of M-estimators in semiparametric models for independent observations to the case of longitudinal data. We approximate the nonparametric function by a regression spline, and any M-estimation algorithm for the usual linear models can then be used to obtain consistent estimators of the model and valid large-sample inferences about the regression parameters without any specification of the error distribution and the covariance structure. Included as special cases are the analysis of the conditional mean and median functions for longitudinal data.