An evaluation of ridge estimator in linear mixed models: an example from kidney failure data
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Publication:5138703
DOI10.1080/02664763.2016.1252732OpenAlexW2546709389MaRDI QIDQ5138703
Publication date: 4 December 2020
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02664763.2016.1252732
Related Items (20)
Ridge estimation in linear mixed measurement error models using generalized maximum entropy ⋮ Kernel Liu prediction approach in partially linear mixed measurement error models ⋮ Kernel estimator and predictor of partially linear mixed-effect errors-in-variables model ⋮ Estimation of parameters in linear mixed measurement error models with stochastic linear restrictions ⋮ The weighted ridge estimation for linear mixed models with measurement error under stochastic linear mixed restrictions ⋮ The new mixed ridge estimator in a linear mixed model with measurement error under stochastic linear mixed restrictions ⋮ Stochastic restricted Liu predictors in linear mixed models ⋮ Stochastic restricted Liu estimator in linear mixed measurement error models ⋮ A further prediction method in linear mixed models: Liu prediction ⋮ Marginal ridge conceptual predictive model selection criterion in linear mixed models ⋮ Influence measures and outliers detection in linear mixed measurement error models with Ridge estimation ⋮ Model selection via conditional conceptual predictive statistic under ridge regression in linear mixed models ⋮ Adaptation of the jackknifed ridge methods to the linear mixed models ⋮ Ridge-GME estimation in linear mixed models ⋮ Principal components regression and \(r-k\) class predictions in linear mixed models ⋮ Model selection in linear mixed-effect models ⋮ The \(\mathrm{r}\)-\(\mathrm{d}\) class predictions in linear mixed models ⋮ Improving prediction by means of a two parameter approach in linear mixed models ⋮ Improvement of mixed predictors in linear mixed models ⋮ Ridge estimation in linear mixed measurement error models with stochastic linear mixed restrictions
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