On the Built-in Restrictions in Linear Mixed Models, with Application to Smoothing Spline Analysis of Variance

被引:2
|
作者
Brumback, Babette A. [1 ]
机构
[1] Univ Florida, Dept Epidemiol & Biostat, Coll Publ Hlth & Hlth Profess, Gainesville, FL 32611 USA
关键词
BLUP; Prediction error variance; REML; Robustly predictable linear combination; Shrinkage; CONSTRAINTS; POPULATION; PREDICTION; REGRESSION; ANOVA; BAYES;
D O I
10.1080/03610920902755847
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The best linear unbiased predictor (BLUP) of the random parameter in a linear mixed model satisfies a linear constraint, which has been previously termed a built-in restriction. In other literature, constraints on the random parameter itself have been introduced into the modeling framework. The present article has two goals. First, it explores the idea of imposing the built-in restrictions on the BLUP as constraints on the random parameter. Second, it investigates the built-in restrictions satisfied by certain smoothing spline analysis of variance (SSANOVA) estimators, and compares these restrictions to arguably more natural side conditions on the ANOVA decomposition.
引用
收藏
页码:579 / 591
页数:13
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