Cross-validation of regression models

Richard R. Picard, R. Dennis Cook

Research output: Contribution to journalArticlepeer-review

964 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 languageEnglish (US)
Pages (from-to)575-583
Number of pages9
JournalJournal of the American Statistical Association
Volume79
Issue number387
DOIs
StatePublished - Sep 1984

Keywords

  • Data splitting
  • Model selection
  • Optimism principle
  • Prediction

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