Iterative weighted partial spline least squares estimation in semiparametric modeling of longitudinal data

被引：0

作者：

孙孝前

尤进红

机构：

[1] Department of Statistics, University of Missouri-Columbia, Columbia, MO 65211, USA ,Department of Mathematics and Statistics, University of Regina, Regina, Saskatchewan, Canada S4S 0A2

[2] Department of Mathematics, Huaiyin Teachers College, Huaian 223001, China

来源：

Science China Mathematics | 2003年 / 05期

关键词：

semiparametric modelling; longitudinal data; iterative weighted partial spline least squares estimator (IWPSLSE); asymptotic normality;

D O I：

暂无

中图分类号：

O211.67 [期望与预测];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper we consider the estimating problem of a semiparametric regression modelling whenthe data are longitudinal.An iterative weighted partial spline least squares estimator(IWPSLSE)for the para-metric component is proposed which is more efficient than the weighted partial spline least squares estimator(WPSLSE)with weights constructed by using the within-group partial spline least squares residuals in the sense

引用

页码：724 / 735

页数：12

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