Penalized least squares for single index models

  title={Penalized least squares for single index models},
  author={Heng Peng and Tao Huang},
The single index model is a useful regression model. In this paper, we propose a nonconcave penalized least squares method to estimate both the parameters and the link function of the single index model. Compared to other variable selection and estimation methods, the proposed method can estimate parameters and select variables simultaneously. When the dimension of parameters in the single index model is a fixed constant, under some regularity conditions, we demonstrate that the proposed… CONTINUE READING
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