Robust conditional nonparametric independence screening for ultrahigh-dimensional data
Shucong Zhang,
Jing Pan and
Yong Zhou
Statistics & Probability Letters, 2018, vol. 143, issue C, 95-101
Abstract:
This article novelly proposes a robust model-free screening procedure, which performs well for a variety of semivarying coefficient models. Under technical conditions, we show that it possesses the ranking consistency property and the sure screening property. Comprehensive simulation studies are conducted to demonstrate that it exhibits more competitive performance than existing screening methods.
Keywords: Feature screening; Semivarying coefficient models; Sure screening property; Ultrahigh-dimensional (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715218302785
Full text for ScienceDirect subscribers only
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: https://EconPapers.repec.org/RePEc:eee:stapro:v:143:y:2018:i:c:p:95-101
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.spl.2018.08.003
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().