Predictive performance of linear regression models

DOI10.1007/s00362-014-0596-4zbMath1309.62115OpenAlexW1988708723MaRDI QIDQ2340401

M. Revan Özkale

Publication date: 16 April 2015

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-014-0596-4

zbMATH Keywords

predictioncross-validationlinear restrictionsLiu estimatorridge estimatortwo parameter estimator

Mathematics Subject Classification ID

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

Related Items (9)

Gilmour's approach to mixed and stochastic restricted ridge predictions in linear mixed models ⋮ Kernel Liu prediction approach in partially linear mixed measurement error models ⋮ Stochastic restricted Liu predictors in linear mixed models ⋮ A further prediction method in linear mixed models: Liu prediction ⋮ Shrinkage parameter selection via modified cross-validation approach for ridge regression model ⋮ Bootstrap selection of ridge regularization parameter: a comparative study via a simulation study ⋮ Cross validation of ridge regression estimator in autocorrelated linear regression models ⋮ Optimal stochastic restricted logistic estimator ⋮ Variable selection in high-dimensional sparse multiresponse linear regression models

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