On admissible invariant estimators of variance components which dominate unbiased invariant estimators
作者:
W. Klonecki,
S. Zontek,
期刊:
Statistics
(Taylor Available online 1987)
卷期:
Volume 18,
issue 4
页码: 483-498
ISSN:0233-1888
年代: 1987
DOI:10.1080/02331888708802046
出版商: Akademie-Verlag
关键词: 62 J 05;Variance components;matrix risk function;admissible invariant estimators;admissible estimators better than unbiased estimators
数据来源: Taylor
摘要:
A characterization of admissible invariant quadratic estimators for linear combinations of variance components for mixed linear models is established.This allows us to construct for the balanced random, one–way ANOVA model, as well as for some other mixed linear models, admissible estimators which are also better than the best unbiased estimator with respect to the matrix risk function. Admissible estimators better than the best unbiased estimator may be used to construt admissible estimators which dominate the unbiased estimators for any parametric function of the variance components.
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