On the mean squared error of the ridge estimator of the covariance and precision matrix

Wessel N. van Wieringen*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates the maximum likelihood regression estimator in terms of the mean squared error. Analogous results for the ridge maximum likelihood estimators of covariance and precision matrix are presented.

Original languageEnglish
Pages (from-to)88-92
Number of pages5
JournalStatistics and Probability Letters
Volume123
DOIs
Publication statusPublished - 1 Apr 2017

Keywords

  • Inverse covariance matrix
  • Multivariate normal
  • ℓ-penalization

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