Envelopes and reduced-rank regression

R. Dennis Cook, Liliana Forzani, Xin Zhang

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

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).

Original languageEnglish (US)
Pages (from-to)439-456
Number of pages18
JournalBiometrika
Volume102
Issue number2
DOIs
StatePublished - Jun 2015

Bibliographical note

Publisher Copyright:
© 2015 Biometrika Trust.

Keywords

  • Envelope model; Grassmannian; Reduced-rank regression

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