Nonparametric estimation in nonlinear mixed effects models

被引：16

作者：

Lai, TL ^{[1
]}

Shih, MC

机构：

[1] Stanford Univ, Dept Stat, Stanford, CA 94305 USA

[2] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA

来源：

BIOMETRIKA | 2003年 / 90卷 / 01期

基金：

美国国家卫生研究院; 美国国家科学基金会;

关键词：

empirical Bayes; mixture likelihood; nonlinear mixed effects model; nonparametric random effects; population pharmacokinetics;

D O I：

10.1093/biomet/90.1.1

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

A nonparametric approach is developed herein to estimate parameters in nonlinear mixed effects models. Asymptotic properties of the nonparametric maximum likelihood estimators and associated computational algorithms are provided. Empirical Bayes estimators of functionals of the random effects are also developed. Applications to population pharmacokinetics are given.

引用

页码：1 / 13

页数：13

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