Characterizing the domain of a regression model

Steven S. Carroll; William A. Verdini

doi:10.1080/00031305.1988.10475559

Characterizing the domain of a regression model

Steven S. Carroll
, William A. Verdini

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

29 Scopus citations

Abstract

Several frequently used estimates of the domain of a regression model are discussed and compared with the convex hull of the predictor-variable values. A simple procedure for identifying new prediction values as interpolation or extrapolation points is presented using the convex hull as the model domain estimate and is illustrated by examples.

Original language	English (US)
Pages (from-to)	187-190
Number of pages	4
Journal	American Statistician
Volume	42
Issue number	3
DOIs	https://doi.org/10.1080/00031305.1988.10475559
State	Published - Aug 1988

Keywords

Convex hull
Extrapolation
Interpolation
Model domain

ASJC Scopus subject areas

Statistics and Probability
General Mathematics
Statistics, Probability and Uncertainty

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10.1080/00031305.1988.10475559

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@article{71dfef1d74c14309829bd8e33051306e,

title = "Characterizing the domain of a regression model",

abstract = "Several frequently used estimates of the domain of a regression model are discussed and compared with the convex hull of the predictor-variable values. A simple procedure for identifying new prediction values as interpolation or extrapolation points is presented using the convex hull as the model domain estimate and is illustrated by examples.",

keywords = "Convex hull, Extrapolation, Interpolation, Model domain",

author = "Carroll, \{Steven S.\} and Verdini, \{William A.\}",

note = "Funding Information: *Daniel G. Brooks is Associate Professor, Steven S. Carroll is Assistant Professor, and William A. Verdini is Associate Professor, all in the De- partment of Decision and Information Systems, Arizona State University, Tempe, Arizona 85287. The authors thank Richard Burdick for helpful comments and the Academic Computing Services at Arizona State University for providing the hardware and software to run the programs in Figure 2. The second author acknowledges partial funding of his work from the Faculty Grant Program of Arizona State University.",

year = "1988",

month = aug,

doi = "10.1080/00031305.1988.10475559",

language = "English (US)",

volume = "42",

pages = "187--190",

journal = "American Statistician",

issn = "0003-1305",

publisher = "Taylor and Francis Ltd.",

number = "3",

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TY - JOUR

T1 - Characterizing the domain of a regression model

AU - Carroll, Steven S.

AU - Verdini, William A.

N1 - Funding Information: *Daniel G. Brooks is Associate Professor, Steven S. Carroll is Assistant Professor, and William A. Verdini is Associate Professor, all in the De- partment of Decision and Information Systems, Arizona State University, Tempe, Arizona 85287. The authors thank Richard Burdick for helpful comments and the Academic Computing Services at Arizona State University for providing the hardware and software to run the programs in Figure 2. The second author acknowledges partial funding of his work from the Faculty Grant Program of Arizona State University.

PY - 1988/8

Y1 - 1988/8

N2 - Several frequently used estimates of the domain of a regression model are discussed and compared with the convex hull of the predictor-variable values. A simple procedure for identifying new prediction values as interpolation or extrapolation points is presented using the convex hull as the model domain estimate and is illustrated by examples.

AB - Several frequently used estimates of the domain of a regression model are discussed and compared with the convex hull of the predictor-variable values. A simple procedure for identifying new prediction values as interpolation or extrapolation points is presented using the convex hull as the model domain estimate and is illustrated by examples.

KW - Convex hull

KW - Extrapolation

KW - Interpolation

KW - Model domain

UR - https://www.scopus.com/pages/publications/0000127755

UR - https://www.scopus.com/pages/publications/0000127755#tab=citedBy

U2 - 10.1080/00031305.1988.10475559

DO - 10.1080/00031305.1988.10475559

M3 - Article

SN - 0003-1305

VL - 42

SP - 187

EP - 190

JO - American Statistician

JF - American Statistician

IS - 3

ER -

Characterizing the domain of a regression model

Abstract

Keywords

ASJC Scopus subject areas

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