Envelopes and reduced-rank regression

被引:27
|
作者
Cook, R. Dennis [1 ]
Forzani, Liliana [2 ]
Zhang, Xin [3 ]
机构
[1] Univ Minnesota, Sch Stat, Minneapolis, MN 55455 USA
[2] Univ Nacl Litoral, RA-3000 Santa Fe, Argentina
[3] Florida State Univ, Dept Stat, Tallahassee, FL 32306 USA
基金
美国国家科学基金会;
关键词
Envelope model; Grassmannian; Reduced-rank regression; ASYMPTOTIC THEORY; ESTIMATOR;
D O I
10.1093/biomet/asv001
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We incorporate the nascent idea of envelopes (Cook et al., Statist. Sinica 20, 927-1010) into reduced-rank regression by proposing a reduced-rank envelope model, which is a hybrid of reduced-rank and envelope regressions. The proposed model has total number of parameters no more than either of reduced-rank regression or envelope regression. The resulting estimator is at least as efficient as both existing estimators. The methodology of this paper can be adapted to other envelope models, such as partial envelopes (Su & Cook, Biometrika 98, 133-46) and envelopes in predictor space (Cook et al., J. R. Statist. Soc. B 75, 851-77).
引用
收藏
页码:439 / 456
页数:18
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