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Nonparametric independence screening via favored smoothing bandwidth. (English) Zbl 1432.62093
Summary: We propose a flexible nonparametric regression method for ultrahigh-dimensional data. As a first step, we propose a fast screening method based on the favored smoothing bandwidth of the marginal local constant regression. Then, an iterative procedure is developed to recover both the important covariates and the regression function. Theoretically, we prove that the favored smoothing bandwidth based screening possesses the model selection consistency property. Simulation studies as well as real data analysis show the competitive performance of the new procedure.

MSC:
62G08 Nonparametric regression and quantile regression
62H12 Estimation in multivariate analysis
62G20 Asymptotic properties of nonparametric inference
62-08 Computational methods for problems pertaining to statistics
Software:
hgam
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