Cross-validation of regression models

Richard R. Picard; R. Dennis Cook

doi:10.1080/01621459.1984.10478083

Cross-validation of regression models

Richard R. Picard, R. Dennis Cook

Statistics (Twin Cities)

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

1246 Scopus citations

Abstract

A methodolgy for assessment of the predictive ability of regression models is presented. Attention is given to models obtained via subset selection procedures, which are extremely difficult to evaluate by standard techniques. Cross-validatory assessments of predictive ability are obtained and their use illustrated in examples.

Original language	English (US)
Pages (from-to)	575-583
Number of pages	9
Journal	Journal of the American Statistical Association
Volume	79
Issue number	387
DOIs	https://doi.org/10.1080/01621459.1984.10478083
State	Published - Sep 1984

Keywords

Data splitting
Model selection
Optimism principle
Prediction

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10.1080/01621459.1984.10478083

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title = "Cross-validation of regression models",

abstract = "A methodolgy for assessment of the predictive ability of regression models is presented. Attention is given to models obtained via subset selection procedures, which are extremely difficult to evaluate by standard techniques. Cross-validatory assessments of predictive ability are obtained and their use illustrated in examples.",

keywords = "Data splitting, Model selection, Optimism principle, Prediction",

author = "Picard, {Richard R.} and Cook, {R. Dennis}",

year = "1984",

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AU - Cook, R. Dennis

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KW - Data splitting

KW - Model selection

KW - Optimism principle

KW - Prediction

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JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

IS - 387

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Cross-validation of regression models

Abstract

Keywords

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