SAVE: A method for dimension reduction and graphics in regression

R. Dennis Cook

doi:10.1080/03610920008832598

SAVE: A method for dimension reduction and graphics in regression

R. Dennis Cook

Statistics (Twin Cities)

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

88 Scopus citations

Abstract

Sliced average variance estimation (SAVE) is a method for constructing sufficient summary plots in regressions with many predictors. The summary plots are designed to capture all the information about the response that is available from the predictors, and do not require a model for their construction. They can be particularly helpful for guiding the choice of a first model. Methodological aspects of SAVE are studied in this article.

Original language	English (US)
Pages (from-to)	2109-2121
Number of pages	13
Journal	Communications in Statistics - Theory and Methods
Volume	29
Issue number	9-10
DOIs	https://doi.org/10.1080/03610920008832598
State	Published - 2000

Bibliographical note

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

Central subspace
Regression graphics
Regression modeling
Sufficient summary plots

Publisher link

10.1080/03610920008832598

Find It

Find It at U of M Libraries

Cite this

@article{5206536778a144399ac10c254ac7a132,

title = "SAVE: A method for dimension reduction and graphics in regression",

abstract = "Sliced average variance estimation (SAVE) is a method for constructing sufficient summary plots in regressions with many predictors. The summary plots are designed to capture all the information about the response that is available from the predictors, and do not require a model for their construction. They can be particularly helpful for guiding the choice of a first model. Methodological aspects of SAVE are studied in this article.",

keywords = "Central subspace, Regression graphics, Regression modeling, Sufficient summary plots",

author = "Cook, {R. Dennis}",

year = "2000",

doi = "10.1080/03610920008832598",

language = "English (US)",

volume = "29",

pages = "2109--2121",

journal = "Communications in Statistics - Theory and Methods",

issn = "0361-0926",

publisher = "Taylor and Francis Ltd.",

number = "9-10",

}

TY - JOUR

T1 - SAVE

T2 - A method for dimension reduction and graphics in regression

AU - Cook, R. Dennis

PY - 2000

Y1 - 2000

N2 - Sliced average variance estimation (SAVE) is a method for constructing sufficient summary plots in regressions with many predictors. The summary plots are designed to capture all the information about the response that is available from the predictors, and do not require a model for their construction. They can be particularly helpful for guiding the choice of a first model. Methodological aspects of SAVE are studied in this article.

AB - Sliced average variance estimation (SAVE) is a method for constructing sufficient summary plots in regressions with many predictors. The summary plots are designed to capture all the information about the response that is available from the predictors, and do not require a model for their construction. They can be particularly helpful for guiding the choice of a first model. Methodological aspects of SAVE are studied in this article.

KW - Central subspace

KW - Regression graphics

KW - Regression modeling

KW - Sufficient summary plots

UR - http://www.scopus.com/inward/record.url?scp=0040753656&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0040753656&partnerID=8YFLogxK

U2 - 10.1080/03610920008832598

DO - 10.1080/03610920008832598

M3 - Article

AN - SCOPUS:0040753656

SN - 0361-0926

VL - 29

SP - 2109

EP - 2121

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 9-10

ER -

SAVE: A method for dimension reduction and graphics in regression

Abstract

Bibliographical note

Keywords

Publisher link

Find It

Other files and links

Fingerprint

Cite this