A ridge-type estimator and good prior means

DOI10.1080/03610928708829583zbMath0651.62068OpenAlexW2006664623MaRDI QIDQ3796577

Jeffrey Pliskin

Publication date: 1987

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928708829583

zbMATH Keywords

shrinkage estimatorsprior informationmean square error matrixordinary ridge regression estimatormodified ridge regression estimator

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (13)

More on the restricted ridge regression estimation ⋮ Some remarks on a ridge-type-estimator and good prior means ⋮ A generalization and Bayesian interpretation of ridge-type estimators with good prior means ⋮ A revised Cholesky decomposition to combat multicollinearity in multiple regression models ⋮ Bayesian ridge regression for survival data based on a vine copula-based prior ⋮ Unbiased ridge estimation with prior information and ridge trace ⋮ Mean squared error comparisons of the modified ridge regression estimator and iiie restricted ridge regression estimator ⋮ Influence in the Elliptical Modified Ridge Regression ⋮ Assessing global influential observations in modified ridge regression ⋮ Combining Unbiased Ridge and Principal Component Regression Estimators ⋮ Local Influence Diagnostics in the Modified Ridge Regression ⋮ Bayesian ridge estimators based on copula-based joint prior distributions for regression coefficients ⋮ Comparisons of the Unbiased Ridge Estimation to the Other Estimations

Cites Work

• Selecting the optimum k in ridge regression
• The Bonferroni and the Scheffe Multiple Comparison Procedures
• Good ridge estimators based on prior information

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