AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (524.9 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

A new measure of partial conditional mean independence in Hilbert spaces

Jiangyuan Bian( )Zhongzhan Zhang
School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing 100124, China
Show Author Information

Abstract

A novel metric, called partial martingale difference-angle divergence, is proposed to test and measure partial conditional mean (in)dependence for Hilbert elements. The partial martingale difference-angle divergence has some appealing properties. It is nonnegative and equals zero if and only if the partial conditional mean independence holds; it has a simple expectation form; it does not require the moment condition for the predictor variable. We construct an estimator for partial martingale difference-angle divergence and derive its asymptotic properties. Finite sample simulations show that the proposed test performs well and has strong testing power for nonlinear relationships. Two real data examples are introduced to illustrate the application of the proposed test.

References

【1】
【1】
 
 
Electronic Research Archive
Pages 411-423

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Bian J, Zhang Z. A new measure of partial conditional mean independence in Hilbert spaces. Electronic Research Archive, 2026, 34(1): 411-423. https://doi.org/10.3934/era.2026019

258

Views

2

Downloads

0

Crossref

0

Web of Science

0

Scopus

Received: 15 November 2025
Revised: 22 December 2025
Accepted: 09 January 2026
Published: 14 January 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)