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• W2546709389 abstract "This paper is concerned with the ridge estimation of fixed and random effects in the context of Henderson's mixed model equations in the linear mixed model. For this purpose, a penalized likelihood method is proposed. A linear combination of ridge estimator for fixed and random effects is compared to a linear combination of best linear unbiased estimator for fixed and random effects under the mean-square error (MSE) matrix criterion. Additionally, for choosing the biasing parameter, a method of MSE under the ridge estimator is given. A real data analysis is provided to illustrate the theoretical results and a simulation study is conducted to characterize the performance of ridge and best linear unbiased estimators approach in the linear mixed model." @default.
• W2546709389 created "2016-11-11" @default.
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• W2546709389 date "2016-11-03" @default.
• W2546709389 modified "2023-10-16" @default.
• W2546709389 title "An evaluation of ridge estimator in linear mixed models: an example from kidney failure data" @default.
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• W2546709389 doi "https://doi.org/10.1080/02664763.2016.1252732" @default.
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