Characterizing the domain of a regression model

Daniel G. Brooks; Steven S. Carroll; William A. Verdini

doi:10.1080/00031305.1988.10475559

Characterizing the domain of a regression model

Daniel G. Brooks, Steven S. Carroll, William A. Verdini

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

19 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
Mathematics(all)
Statistics, Probability and Uncertainty

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10.1080/00031305.1988.10475559

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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.",

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