Testing independence in the presence of missing data: high-dimensional case
Methodology
2026-04-28 v1 Statistics Theory
Statistics Theory
Abstract
In this paper, we consider the problem of testing independence in high-dimensional settings with missing data. Building upon a recently proposed Kendall-based statistic, we introduce two new modifications specifically designed to accommodate incomplete observations. The proposed methods are studied from both theoretical and empirical perspectives. A comprehensive simulation study illustrates the robustness and applicability of the new approaches. The findings contribute to the development of nonparametric methods for analyzing high-dimensional and incomplete data structures.
Cite
@article{arxiv.2604.22980,
title = {Testing independence in the presence of missing data: high-dimensional case},
author = {Marija Cuparić and Bojana Milošević and Jelena Radojević},
journal= {arXiv preprint arXiv:2604.22980},
year = {2026}
}