Please use this identifier to cite or link to this item: http://buratest.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

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