Classification with incomplete functional covariates

Majid Mojirsheibani and Crystal Shaw

Statistics & Probability Letters, 2018, vol. 139, issue C, 40-46

Abstract: We consider the problem of functional classification when the covariate may be unavailable (unobservable) on some subsets of its domain. Given the observed fragments of the functional covariates, we propose a strongly consistent nonparametric classifier based on local averaging.

Keywords: Classification; Pattern recognition; Functional covariates; Supervised learning (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715218301305
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:139:y:2018:i:c:p:40-46

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.2018.03.010

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 ().