A note on fast envelope estimation

R. Dennis Cook; Liliana Forzani; Zhihua Su

doi:10.1016/j.jmva.2016.05.006

A note on fast envelope estimation

R. Dennis Cook, Liliana Forzani, Zhihua Su

Statistics (Twin Cities)

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Abstract

We propose a new algorithm for envelope estimation, along with a new n-consistent method for computing starting values. The new algorithm, which does not require optimization over a Grassmannian, is shown by simulation to be much faster and typically more accurate than the best existing algorithm proposed by Cook and Zhang (2016).

Original language	English (US)
Pages (from-to)	42-54
Number of pages	13
Journal	Journal of Multivariate Analysis
Volume	150
DOIs	https://doi.org/10.1016/j.jmva.2016.05.006
State	Published - 2016

Bibliographical note

Funding Information:
The authors thank Hongtu Zhu for providing the Alzheimer data and Nadia L. Kudraszow for providing the glass data. The authors also thank the Editor and two Associate Editors for an incredibly fast review, faster than we have ever experienced before. Research for this article was supported in part by grant DMS-1407460 from the National Science Foundation .

Publisher Copyright:
© 2016 Elsevier Inc.

Keywords

Envelopes
Grassmann manifold
Reducing subspaces

Publisher link

10.1016/j.jmva.2016.05.006

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title = "A note on fast envelope estimation",

abstract = "We propose a new algorithm for envelope estimation, along with a new n-consistent method for computing starting values. The new algorithm, which does not require optimization over a Grassmannian, is shown by simulation to be much faster and typically more accurate than the best existing algorithm proposed by Cook and Zhang (2016).",

keywords = "Envelopes, Grassmann manifold, Reducing subspaces",

author = "Cook, {R. Dennis} and Liliana Forzani and Zhihua Su",

note = "Funding Information: The authors thank Hongtu Zhu for providing the Alzheimer data and Nadia L. Kudraszow for providing the glass data. The authors also thank the Editor and two Associate Editors for an incredibly fast review, faster than we have ever experienced before. Research for this article was supported in part by grant DMS-1407460 from the National Science Foundation . Publisher Copyright: {\textcopyright} 2016 Elsevier Inc.",

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doi = "10.1016/j.jmva.2016.05.006",

language = "English (US)",

volume = "150",

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AU - Cook, R. Dennis

AU - Forzani, Liliana

AU - Su, Zhihua

N1 - Funding Information: The authors thank Hongtu Zhu for providing the Alzheimer data and Nadia L. Kudraszow for providing the glass data. The authors also thank the Editor and two Associate Editors for an incredibly fast review, faster than we have ever experienced before. Research for this article was supported in part by grant DMS-1407460 from the National Science Foundation . Publisher Copyright: © 2016 Elsevier Inc.

PY - 2016

Y1 - 2016

N2 - We propose a new algorithm for envelope estimation, along with a new n-consistent method for computing starting values. The new algorithm, which does not require optimization over a Grassmannian, is shown by simulation to be much faster and typically more accurate than the best existing algorithm proposed by Cook and Zhang (2016).

AB - We propose a new algorithm for envelope estimation, along with a new n-consistent method for computing starting values. The new algorithm, which does not require optimization over a Grassmannian, is shown by simulation to be much faster and typically more accurate than the best existing algorithm proposed by Cook and Zhang (2016).

KW - Envelopes

KW - Grassmann manifold

KW - Reducing subspaces

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JO - Journal of Multivariate Analysis

JF - Journal of Multivariate Analysis

SN - 0047-259X

ER -

A note on fast envelope estimation

Abstract

Bibliographical note

Keywords

Publisher link

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