A note on combining ridge and principal component regression

DOI10.1080/03610928508829057zbMath0592.62063OpenAlexW2075249013MaRDI QIDQ3721629

Masuo Nomura, Tsuneharu Ohkubo

Publication date: 1985

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

Full work available at URL: https://doi.org/10.1080/03610928508829057

zbMATH Keywords

mean square errorordinary least squaresOLSprincipal components regressionr-k class estimatorordinary ridge regression

Mathematics Subject Classification ID

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

Related Items (19)

Combining neural networks for function approximation under conditions of sparse data: the biased regression approach ⋮ COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR ⋮ A class of biased estimators based on QR decomposition ⋮ Comparisons among some estimators in misspecified linear models with multicollinearity ⋮ Superiority of ther–kClass Estimator Over Some Estimators In A Linear Model ⋮ Optimal QR-based estimation in partially linear regression models with correlated errors using GCV criterion ⋮ Superiority of the \(r\)-\(d\) class estimator over some estimators by the mean square error matrix criterion ⋮ Mean square error matrix comparison of some estimators in linear regressions with multicollinearity ⋮ Combining two-parameter and principal component regression estimators ⋮ A revised Cholesky decomposition to combat multicollinearity in multiple regression models ⋮ Comparisons of the \(r\)-\(k\) class estimator to the ordinary least squares estimator under the Pitman's closeness criterion ⋮ Combining the unrestricted estimators into a single estimator and a simulation study on the unrestricted estimators ⋮ Combining the Liu-type estimator and the principal component regression estimator ⋮ Modified and Restricted r-k Class Estimators ⋮ Efficiency of the QR class estimator in semiparametric regression models to combat multicollinearity ⋮ \(r\)-\(k\) class estimator in the linear regression model with correlated errors ⋮ Evaluation of the predictive performance of the r-k and r-d class estimators ⋮ \(r-k\) class estimation in regression model with concomitant variables ⋮ An optimal property of the “(r,k ) class estimators”

Cites Work

• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation

This page was built for publication: A note on combining ridge and principal component regression