Weighted composite quantile regression for single index model with missing covariates at random

Huilan Liu (), Hu Yang and Changgen Peng
Additional contact information
Huilan Liu: Guizhou University
Hu Yang: Chongqing University
Changgen Peng: Guizhou University

Computational Statistics, 2019, vol. 34, issue 4, No 13, 1740 pages

Abstract: Abstract This paper considers weighted composite quantile estimation of the single-index model with missing covariates at random. Under some regularity conditions, we establish the large sample properties of the estimated index parameters and link function. The large sample properties of the parametric part show that the estimator with estimated selection probability have a smaller limiting variance than the one with the true selection probability. However, the large sample properties of the estimated link function indicate that whether weights were estimated or not has no effect on the asymptotic variance. Studies of simulation and the real data analysis are presented to illustrate the behavior of the proposed estimators.

Keywords: Horvitz–Thompson property; Local linear regression; Missing at random (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s00180-019-00886-y 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: https://EconPapers.repec.org/RePEc:spr:compst:v:34:y:2019:i:4:d:10.1007_s00180-019-00886-y

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2

DOI: 10.1007/s00180-019-00886-y

Access Statistics for this article

Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik

More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().