Abstract:
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The performance of penalized methods greatly depends on choice of the tuning parameter. Most existing methods select a single optimal tuning parameter which minimize some criteria, e.g, AIC or BIC. However, it is not intuitive to interpret the tuning parameter selected or the model selected. We propose a new method based on phony variables to choose the tuning parameter. It has asymptotic selection consistency. In addition, it controls error rate for variable selection and outperforms other methods.
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