Ridge regression and its degrees of freedom

Theo K. Dijkstra*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)

Abstract

For ridge regression the degrees of freedom are commonly calculated by the trace of the matrix that transforms the vector of observations on the dependent variable into the ridge regression estimate of its expected value. For a fixed ridge parameter this is unobjectionable. When the ridge parameter is optimized on the same data, by minimization of the generalized cross validation criterion or Mallows , additional degrees of freedom are used however. We give formulae that take this into account. This allows of a proper assessment of ridge regression in competitions for the best predictor.

Original languageEnglish
Pages (from-to)3185-3193
Number of pages9
JournalQuality and Quantity
Volume48
Issue number6
DOIs
Publication statusPublished - Nov-2014

Keywords

  • Ridge regression
  • Degrees of freedom
  • Prediction
  • Cross-validation
  • Stein's identity
  • GENERALIZED CROSS-VALIDATION

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