ASQ

Exclusive Content & Downloads from ASQ

Robust Ridge Regression for High-Dimensional Data

Summary: [This abstract is based on the authors' abstract.] Ridge regression is sensitive to outliers, and existing proposals for robust estimators decrease in robustness as the number of predictors approaches the number of observations until they become nonviable when the number of predictors exceeds the number of observations. This article proposes a ridge regression estimate based on multiple M (MM) estimation. This estimate maintains robustness as the number of predictors approaches and exceeds the number of observations. Examples are presented using both simulated and real data.

Anyone with a subscription, including Site and Enterprise members, can access this article.


Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

  • Topics: Statistics
  • Keywords: Estimation, Regression, Ridge analysis
  • Author: Maronna, Ricardo A.
  • Journal: Technometrics