Test of partial effects for Fréchet regression on Bures-Wasserstein manifolds

Abstract We propose a novel test for assessing partial effects in Fréchet regression on the Bures-Wasserstein manifold. Under the null hypothesis, we show that the statistic admits a degenerate V-statistic approximation whose limiting distribution is aweighted mixture of chi-squared random variables, with weights determined by the eigenvalues of an integral operator associated with a reproducing kernel Hilbert space (RKHS) kernel. We establish the asymptotic validity and consistency of the proposed test. Its finite-sample performance is examined through simulation studies.We apply the proposed test to study the effect of age, while controlling for other covariates, on gene co-expression structure in single-cell data.

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Publication Details

Journal
Biometrika
Published
2026-10-26
DOI
https://doi.org/10.1093/biomet/asag064
Primary Topic
Advanced Statistical Methods and Models
Type
article
Field-Weighted Citation Impact
0.00

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article

Test of partial effects for Fréchet regression on Bures-Wasserstein manifolds

Haotian Xu, Hongzhe Li
Biometrika
Advanced Statistical Methods and Models
article

Test of partial effects for Fréchet regression on Bures-Wasserstein manifolds

Haotian Xu, Hongzhe Li
article en

Abstract

Abstract We propose a novel test for assessing partial effects in Fréchet regression on the Bures-Wasserstein manifold. Under the null hypothesis, we show that the statistic admits a degenerate V-statistic approximation whose limiting distribution is aweighted mixture of chi-squared random variables, with weights determined by the eigenvalues of an integral operator associated with a reproducing kernel Hilbert space (RKHS) kernel. We establish the asymptotic validity and consistency of the proposed test. Its finite-sample performance is examined through simulation studies.We apply the proposed test to study the effect of age, while controlling for other covariates, on gene co-expression structure in single-cell data.

Biometrika
University of Pennsylvania (US)
National Institutes of Health
Openalex Percentile: Top 95%
Advanced Statistical Methods and Models
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