Exponential dimensional dependence in high-dimensional Hermite method of moments

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Hauptverfasser: Basse-O'Connor, Andreas, Kramer-Bang, David
Format: Preprint
Veröffentlicht: 2025
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author Basse-O'Connor, Andreas
Kramer-Bang, David
author_facet Basse-O'Connor, Andreas
Kramer-Bang, David
contents It is numerically well known that moment-based tests for Gaussianity and estimators become increasingly unreliable at higher moment orders; however, this phenomenon has lacked rigorous mathematical justification. In this work, we establish quantitative bounds for Hermite-based moment tests, with matching exponential upper and lower bounds. Our results show that, even under ideal conditions with i.i.d. standard normal data, the sample size must grow exponentially with the highest moment order $d$ used in the test. These bounds, derived under both the convex distance and the Kolmogorov-Smirnov distance, are applied to classical procedures, such as the Shenton-Bowman test.
format Preprint
id arxiv_https___arxiv_org_abs_2502_17431
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Exponential dimensional dependence in high-dimensional Hermite method of moments
Basse-O'Connor, Andreas
Kramer-Bang, David
Statistics Theory
Probability
60H07, 60F05, 60G15
It is numerically well known that moment-based tests for Gaussianity and estimators become increasingly unreliable at higher moment orders; however, this phenomenon has lacked rigorous mathematical justification. In this work, we establish quantitative bounds for Hermite-based moment tests, with matching exponential upper and lower bounds. Our results show that, even under ideal conditions with i.i.d. standard normal data, the sample size must grow exponentially with the highest moment order $d$ used in the test. These bounds, derived under both the convex distance and the Kolmogorov-Smirnov distance, are applied to classical procedures, such as the Shenton-Bowman test.
title Exponential dimensional dependence in high-dimensional Hermite method of moments
topic Statistics Theory
Probability
60H07, 60F05, 60G15
url https://arxiv.org/abs/2502.17431