Salvato in:
Dettagli Bibliografici
Autori principali: Zhang, Yan, Volgushev, Stanislav
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:https://arxiv.org/abs/2604.12087
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866913028927127552
author Zhang, Yan
Volgushev, Stanislav
author_facet Zhang, Yan
Volgushev, Stanislav
contents We study the nonparametric maximum likelihood estimator (NPMLE) for Gaussian and Poisson mixture models, assuming the support of the true mixing distribution lies in a fixed bounded set. In this setting, we establish exact parametric rates for both, marginal density estimation and the posterior mean when the true mixing distribution is finitely discrete. Moreover, we show that the NPMLE attains the optimal demixing rate previously known for overparameterized finite mixture models. Finally, we identify a new adaptivity phenomenon for inference: the likelihood ratio test statistic is asymptotically tight if and only if the true mixing distribution is finitely discrete.
format Preprint
id arxiv_https___arxiv_org_abs_2604_12087
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Adaptivity of the NPMLE to finitely discrete mixing distributions in Gaussian/Poisson mixtures
Zhang, Yan
Volgushev, Stanislav
Statistics Theory
We study the nonparametric maximum likelihood estimator (NPMLE) for Gaussian and Poisson mixture models, assuming the support of the true mixing distribution lies in a fixed bounded set. In this setting, we establish exact parametric rates for both, marginal density estimation and the posterior mean when the true mixing distribution is finitely discrete. Moreover, we show that the NPMLE attains the optimal demixing rate previously known for overparameterized finite mixture models. Finally, we identify a new adaptivity phenomenon for inference: the likelihood ratio test statistic is asymptotically tight if and only if the true mixing distribution is finitely discrete.
title Adaptivity of the NPMLE to finitely discrete mixing distributions in Gaussian/Poisson mixtures
topic Statistics Theory
url https://arxiv.org/abs/2604.12087