On a nonparametric notion of residual and its applications
Rohit K. Patra,
Bodhisattva Sen and
Gábor J. Székely
Statistics & Probability Letters, 2016, vol. 109, issue C, 208-213
Abstract:
Given a random vector (X,Z), we define a notion of nonparametric residual of X on Z that is always independent of Z. Given (X,Y,Z), we use this notion of residual to develop a test for the conditional independence between X and Y, given Z.
Keywords: Conditional distribution function; Testing conditional independence (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715215301930
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:109:y:2016:i:c:p:208-213
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.2015.10.011
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 ().