\(r-k\) class estimation in regression model with concomitant variables

DOI10.1007/BF00049291zbMath0860.62054OpenAlexW2157360465MaRDI QIDQ1817410

Nobuo Inagaki, Masayuki Jimichi

Publication date: 1 December 1996

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00049291

zbMATH Keywords

multicollinearityordinary least squares estimatorconcomitant variablesprincipal component regression estimatormisspecified linear modelordinary ridge regression estimatorr-k class estimationtotal mean square error

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items

Performance of the principal component two-parameter estimator in misspecified linear regression model ⋮ On the restrictedr–kclass estimator and the restrictedr–dclass estimator in linear regression ⋮ r-d Class Estimator Under Misspecification ⋮ Superiority of the r-k class estimator over some estimators in a misspecified linear model

Cites Work

• Comparisons among some estimators in misspecified linear models with multicollinearity
• An optimal property of the “(r,k ) class estimators”
• Studies in the history of probability and statistics. V. A note on playing cards
• A note on combining ridge and principal component regression
• A simulation study of ridge and other regression estimators
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
• Linear Statistical Inference and its Applications