Economics at your fingertips  

B spline variable selection for the single index models

Jianbo Li (), Yuan Li and Riquan Zhang
Additional contact information
Jianbo Li: Guangzhou University
Yuan Li: Guangzhou University
Riquan Zhang: East China Normal University

Statistical Papers, 2017, vol. 58, issue 3, 691-706

Abstract: Abstract Through the nonconcave penalized least squares method, we consider the variable selection in the full nonparametric regression models with the B spline-based single index approximation. Under some regular conditions, we show that the resulting estimates with SCAD and HARD thresholding penalties enjoy $$\sqrt{n}$$ n -consistency and oracle properties. We use some simulation studies and a real example to illustrate the performance of our proposed variable selection procedure.

Keywords: Single index model; Lasso; SCAD; Hard Thresholding; Oracle; Primary 62G08; Secondary 62H12 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362

Access Statistics for this article

Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller

More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla ().

Page updated 2019-04-09
Handle: RePEc:spr:stpapr:v:58:y:2017:i:3:d:10.1007_s00362-015-0721-z