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Weighted Score Matching on Bounded Domains: Nonparametric Density Estimation and Interaction Graph Recovery — arXiv:2610.39335

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.39335
License (as archived): CC0-1.0
Archived: 2026-11-01T02:31:11.679Z
SHA-256 of the archived text: d1847a5f8e1990aeae18edc5a76ef950cac4bb2657ea91c6b747f74672eabd4d
Stable URL of this page: https://metraipolis.com/documento/dc_4e6aec182eac

How to cite

Weighted Score Matching on Bounded Domains: Nonparametric Density Estimation and Interaction Graph Recovery — arXiv:2610.39335 — arXiv (en), https://arxiv.org/abs/2610.39335 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_4e6aec182eac (Metraipolis archive dc_4e6aec182eac, sha256 d1847a5f8e1990aeae18edc5a76ef950cac4bb2657ea91c6b747f74672eabd4d)

BibTeX

@misc{dc4e6aec182eac,
  title = {Weighted Score Matching on Bounded Domains: Nonparametric Density Estimation and Interaction Graph Recovery — arXiv:2610.39335},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.39335},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_4e6aec182eac; sha256 d1847a5f8e1990aeae18edc5a76ef950cac4bb2657ea91c6b747f74672eabd4d},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.39335. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

We study nonparametric density estimation and interaction-graph recovery on bounded product domains using boundary-weighted score matching. In a canonically centered pairwise log-density model, graph edges are determined by bivariate interactions, but penalizing the univariate main effects can induce false edges. We derive the resulting shift in interaction scores and study partially penalized weighted score matching (P-WSM), which leaves main effects unpenalized. At the population level, P-WSM excludes edges between independent subsystems even when the marginal log densities are not represented exactly by the sieve. A nonparametric construction separates partial and joint penalization: throughout a common deterministic tuning interval, P-WSM recovers the graph while joint penalization selects a false edge. We also give growing-dimensional recovery conditions that do not require full-Gram invertibility. For density estimation at fixed dimension, we establish weighted Fisher-divergence rates and, under stronger basis-specific conditions, Kullback-Leibler and Hellinger rates for the normalized estimator. Simulations examine the benefits and limitations of partial penalization. An analysis of bone-marrow signaling data illustrates nonlinear conditional-association estimation.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv stat.ME, nuovi lavori del giorno).
Categorie arXiv: Methodology (stat.ME).
Pagina del lavoro: https://arxiv.org/abs/2610.39335 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-01T02:13:43.980Z dalla pagina https://arxiv.org/list/stat.ME/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).