Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415357 | Computational Statistics & Data Analysis | 2008 | 16 Pages |
Abstract
The problem of automatic bandwidth selection in nonparametric regression is considered when a local linear estimator is used to derive nonparametrically the unknown regression function. A plug-in method for choosing the smoothing parameter based on the use of the neural networks is presented. The method applies to dependent data generating processes with nonlinear autoregressive time series representation. The consistency of the method is shown in the paper, and a simulation study is carried out to assess the empirical performance of the procedure.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
F. Giordano, M.L. Parrella,