Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/11595
Title: | Robust variable selection in partially varying coefficient single-index model |
Authors: | Zhu, H Lv, Z Yu, K Deng, C |
Keywords: | Variable selection;Spline approximation;Modal regression;SCAD;Oracle property |
Issue Date: | 2015 |
Publisher: | Elsevier |
Citation: | Journal of the Korean Statistical Society, 44(1): pp. 45 - 57, (2015) |
Abstract: | By combining basis function approximations and smoothly clipped absolute deviation (SCAD) penalty, this paper proposes a robust variable selection procedure for a partially varying coefficient single-index model based on modal regression. The proposed procedure simultaneously selects significant variables in the parametric components and the nonparametric components. With appropriate selection of the tuning parameters, we establish the theoretical properties of our procedure, including consistency in variable selection and the oracle property in estimation. Furthermore, we also discuss the bandwidth selection and propose a modified expectation-maximization (EM)-type algorithm for the proposed estimation procedure. The finite sample properties of the proposed estimators are illustrated by some simulation examples. |
URI: | http://www.sciencedirect.com/science/article/pii/S1226319214000428 http://bura.brunel.ac.uk/handle/2438/11595 |
DOI: | http://dx.doi.org/10.1016/j.jkss.2014.05.002 |
ISSN: | 1226-3192 |
Appears in Collections: | Dept of Mathematics Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Fulltext.pdf | 320.99 kB | Adobe PDF | View/Open |
Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.