The relative efficiency of the restricted estimators in linear regression models

DOI10.1080/02664763.2013.859234zbMath1352.62113OpenAlexW2113959502MaRDI QIDQ3179215

M. Revan Özkale

Publication date: 21 December 2016

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2013.859234

zbMATH Keywords

mean square errorlinear restrictionsrestricted ridge regression estimatorrestricted least squares estimatorrestricted two parameter estimator

Mathematics Subject Classification ID

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

Related Items (7)

Estimation of parameters in linear mixed measurement error models with stochastic linear restrictions ⋮ Restricted ridge estimator in generalized linear models: Monte Carlo simulation studies on Poisson and binomial distributed responses ⋮ Diagnostic measures for the restricted Liu estimator in linear measurement error models ⋮ Optimal determination of the parameters of some biased estimators using genetic algorithm ⋮ Estimation in a linear regression model with stochastic linear restrictions: a new two-parameter-weighted mixed estimator ⋮ Unnamed Item ⋮ Iterative restricted OK estimator in generalized linear models and the selection of tuning parameters via MSE and genetic algorithm

Cites Work

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• Combining the unrestricted estimators into a single estimator and a simulation study on the unrestricted estimators
• More on the restricted ridge regression estimation
• The Restricted and Unrestricted Two-Parameter Estimators
• A Test of the Mean Square Error Criterion for Restrictions in Linear Regression
• Numerical inverting of matrices of high order

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