Name
Abstract | ||
|---|---|---|
In this article, we study a general single-index model with diverging number of predictors by using the adaptive Elastic-Net inverse regression method. The proposed method not only can estimate the direction of index and select important variables simultaneously, but also can avoid to estimate the unknown link function through nonparametric method. Under some regularity conditions, we show that the proposed estimators enjoy the so-called oracle property. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-22833-9_62 | NONLINEAR MATHEMATICS FOR UNCERTAINTY AND ITS APPLICATIONS |
Keywords | Field | DocType |
Elastic-Net,Single-index Model,Inverse regression,High dimensionality,Dimension reduction,Variable Selection,Oracle property | Multivariate adaptive regression splines,Errors-in-variables models,Applied mathematics,Regression analysis,Elastic net regularization,Regression diagnostic,Nonparametric regression,Polynomial regression,Local regression,Mathematics | Conference |
Volume | Issue | ISSN |
100 | null | 1867-5662 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuejing Li | 1 | 0 | 1.01 |
| Gaorong Li | 2 | 64 | 14.58 |
| Suigen Yang | 3 | 0 | 0.68 |