Nonparametric local linear estimation of the relative error regression function for twice censored data

Bouhadjera Feriel and Ould Saïd Elias

Statistics & Probability Letters, 2021, vol. 178, issue C

Abstract: This paper deals with the problem of nonparametric relative error regression function estimation for twice censored data. A new estimate is proposed, which is built by combining the local linear approach and relative error estimation. A uniform almost sure consistency with rate over a compact set is established. A numerical study is carried out to assess the performance of the proposed estimator. Practical results indicate the robustness of the new estimate compared to other existing estimators in the presence of censored and outliers datum.

Keywords: Local linear estimation; Regression function; Relative error; Twice censored data; Uniform almost sure consistency (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715221001474
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:178:y:2021:i:c:s0167715221001474

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.2021.109185

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 ().