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An improved model averaging scheme for logistic regression. (English) Zbl 1163.62029

Summary: Recently, penalized regression methods have attracted much attention in the statistical literature. We argue that such methods can be improved for the purposes of prediction by utilizing model averaging ideas. We propose a new algorithm that combines penalized regression with model averaging for improved prediction. We also discuss the issue of model selection versus model averaging and propose a diagnostic based on the notion of generalized degrees of freedom. The proposed methods are studied using both simulated and real data.

MSC:

62G08 Nonparametric regression and quantile regression
65C60 Computational problems in statistics (MSC2010)
62G99 Nonparametric inference
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References:

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