Algorithms for Envelope Estimation

R. Dennis Cook, Xin Zhang

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Envelopes were recently proposed as methods for reducing estimative variation in multivariate linear regression. Estimation of an envelope usually involves optimization over Grassmann manifolds. We propose a fast and widely applicable one-dimensional (1D) algorithm for estimating an envelope in general. We reveal an important structural property of envelopes that facilitates our algorithm, and we prove both Fisher consistency and (Formula presented.) -consistency of the algorithm. Supplementary materials for this article are available online.

Original languageEnglish (US)
Pages (from-to)284-300
Number of pages17
JournalJournal of Computational and Graphical Statistics
Volume25
Issue number1
DOIs
StatePublished - Jan 2 2016

Fingerprint

Envelope
Grassmann Manifold
Linear regression
Structural Properties
Optimization
Structural properties

Keywords

  • Envelopes
  • Grassmann manifold
  • Reducing subspaces

Cite this

Algorithms for Envelope Estimation. / Cook, R. Dennis; Zhang, Xin.

In: Journal of Computational and Graphical Statistics, Vol. 25, No. 1, 02.01.2016, p. 284-300.

Research output: Contribution to journalArticle

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