Comparisons among some estimators in misspecified linear models with multicollinearity

DOI10.1007/BF00057737zbMath0721.62065MaRDI QIDQ2641042

Nityananda Sarkar

Publication date: 1989

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

zbMATH Keywords

linear modelmean square errormisspecificationmulticollinearityordinary least squares estimatorprincipal component regression estimatorordinary ridge regression estimatorcomparisons among several estimatorspredictor of the conditional mean of the dependent variabler-k class estimator

Mathematics Subject Classification ID

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

Related Items (7)

Stochastic restricted biased estimators in misspecified regression model with incomplete prior information ⋮ On equalities for BLUEs under misspecified Gauss-Markov models ⋮ Mean square error matrix comparison of some estimators in linear regressions with multicollinearity ⋮ r-d Class Estimator Under Misspecification ⋮ Superiority of the r-k class estimator over some estimators in a misspecified linear model ⋮ Weighted least squares estimators in possibly misspecified nonlinear regression ⋮ \(r-k\) class estimation in regression model with concomitant variables

Cites Work

• A note on combining ridge and principal component regression
• An Optimal Property of Principal Components in the Context of Restricted Least Squares
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
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