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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.
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页码:579 / 591
页数:13
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