CAJ | 학술논문

本文考虑了纵向数据的部分线性模型.在考虑个体内部相关性的情况下,研究了回归系数的经验似然推断.对于任意的工作协方差矩阵,所给的经验似然比统计量服从渐近卡方分布,由此可以构造回归参数的置信域.模拟结果表明,在正确指定个体相关结构的情况下,推断的效率会显著的提高.最后,给出了案例分析.
본문고필료종향수거적부분선성모형.재고필개체내부상관성적정황하,연구료회귀계수적경험사연추단.대우임의적공작협방차구진,소급적경험사연비통계량복종점근잡방분포,유차가이구조회귀삼수적치신역.모의결과표명,재정학지정개체상관결구적정황하,추단적효솔회현저적제고.최후,급출료안례분석.
Longitudinal data arises when subjects are followed over a period time.In this paper,we applied block empirical likelihood in partially linear regression model accounting for the withinsubject correlation.For any working covariance matrix,an empirical log-likelihood ratio for the parametric components,which are of primary interest,is proposed,and the nonparametric version of the Wilk's theorem is derived.Simulations show that performance can be substantially improved by correctly specifying the correlation structure.At last,we illustrate the proposed method by analyzing an example in epidemiology.