A test of the mean square error criterion for shrinkage estimators

DOI10.1080/03610918208812274zbMath0539.62080OpenAlexW2038607217MaRDI QIDQ3326648

Erkki P. Liski

Publication date: 1982

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918208812274

zbMATH Keywords

simulationshrinkage estimatorridge regressionleast squares estimatorlinear admissible estimatorscentral-F approximations

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items (8)

The relative efficiency of the restricted estimators in linear regression models ⋮ A test of the mean square error criterion for linear admissible estimators ⋮ A test statistic to choose between Liu-type and least-squares estimator based on mean square error criteria ⋮ On the performance of biased estimators in the linear regression model with correlated or heteroscedastic errors ⋮ The Restricted and Unrestricted Two-Parameter Estimators ⋮ Estimation of the signal-to-noise in the linear regression model ⋮ Some Shrinkage estimators based on median ranked set sampling ⋮ Another look at the naive estimator in a regression model

Cites Work

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• Estimation of parameters in a linear model
• A Note on the Generation of Random Normal Deviates
• A mean square error test when stochastic restrictions are used in regression
• A Test of the Mean Square Error Criterion for Restrictions in Linear Regression

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