基于变系数模型的纵向数据相关结构选择和估计

Correlation Structure Selection for Longitudinal Data Based on Varying-Coefficient Model

  • 摘要: 本文针对基于变系数模型的纵向数据提出选择和估计其个体内部相关结构的方法, 给出变系数模型中系数函数曲线的有效估计, 并建立相应的大样本渐近性质. 模拟结果和实例分析表明, 即使在有限样本下, 本文所提方法在选择和估计真实相关结构方面具有相合性, 并能够提高系数函数曲线的估计效率.

     

    Abstract: In this article, we propose an efficient method to identify an informative correlation structure for longitudinal data based on varying-coefficient models and the proposed approach yields a more efficient estimator for the coefficient curves. Simulation and real data example show that the proposed method has efficiency in selecting and estimating the true correlation structure in finite samples and the estimation efficiency of the coefficient curves is improved by using the selected correlation structure in the estimation procedure.

     

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