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Variable Selection and Shrinkage: Comparison of Some Approaches

机译：变量选择和收缩：几种方法的比较

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摘要

A common strategy within the framework of regression models is the selection of variables with possible predictive value, which are incorporated in the regression model. Two recently proposed methods, Breiman's Garotte (Breiman, 1995) and Tibshirani's Lasso (Tibshirani, 1996) try to combine variable selection and shrinkage. We compare these with pure variable selection and shrinkage procedures. We consider the backward elimination procedure as a typical variable selection procedure and as an example of a shrinkage procedure an approach of Van Houwelingen and Le Cessie (1990). Additionally an extension of van Houwelingens and le Cessies approach proposed by Sauerbrei (1999) is considered. The ordinary least squares method is used as a reference.With the help of a simulation study we compare these approaches with respect to the distribution of the complexity of the selected model, the distribution of the shrinkage factors, selection bias, the bias and variance of the effect estimates and the average prediction error.
机译：回归模型框架内的常见策略是选择具有可能的预测值的变量，这些变量将并入回归模型。最近提出的两种方法，Breiman的Garotte（Breiman，1995）和Tibshirani的Lasso（Tibshirani，1996）试图将变量选择和收缩结合起来。我们将它们与纯变量选择和收缩过程进行比较。我们将后向消除过程视为典型的变量选择过程，并将收缩过程的示例视为Van Houwelingen和Le Cessie（1990）的方法。另外，还考虑了Sauerbrei（1999）提出的van Houwelingens和le Cessies方法的扩展。普通最小二乘法被作为参考。在仿真研究的帮助下，我们将这些方法与所选模型的复杂度分布，收缩系数的分布，选择偏差，偏差和方差进行了比较。效果估计和平均预测误差。

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  • 来源
    《Statistica neerlandica》 |2001年第1期|53-75|共23页
  • 作者

    K. Vach; W. Sauerbrei; M. Schumacher;

  • 作者单位

    Department of Statistics and Demography University of Southern Denmark and Institute of Medical Biometry and Informatics Center for Data Analysis and Model Building University of Freiburg Germany;

    Institute of Medical Biometry and Informatics University of Freiburg Germany;

    Institute of Medical Biometry and Informatics University of Freiburg Freiburg Germany Center for Data Analysis and Model Building University of Freiburg Germany;

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  • 正文语种 eng
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  • 关键词

    selection bias; linear regression; prediction error;

    机译：选择偏差;线性回归;预测误差;

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