pith:UXUES5S4
Multivariate EDF tests for uniformity, normality,spherical and elliptical symetry, and independence based on a Brownian sheet deconstruction
New EDF tests reduce multivariate normality, symmetry, and independence checks to uniformity testing on the unit hypercube via Brownian sheet decomposition.
arxiv:2605.17474 v1 · 2026-05-17 · math.ST · stat.ME · stat.TH
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Claims
Empirical power comparisons show that these extended procedures are highly competitive with existing methods in the statistical literature, demonstrating particular sensitivity to coordinate-based dependencies and joint dependency structures.
Whenever a null hypothesis implies a joint distribution that factorizes into independent continuous components after a suitable mapping, the problem can be reduced to a uniformity test on the hypercube via componentwise probability integral transforms.
Extends m-test and s-test via Brownian sheet deconstruction to new EDF procedures for uniformity on S^p, multivariate normality, symmetry, and independence, with competitive empirical power.
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| First computed | 2026-05-20T00:04:40.878147Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
a5e849765ccdd001efa2fbc53b480598b81351125f863a995857ebfb2ba06283
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/UXUES5S4ZXIAD35C7PCTWSAFTC \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
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Canonical record JSON
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