Central limit theorems associated with the hierarchical Dirichlet process

Fuente: arXiv
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Auteurs principaux: Feng, Shui, Paguyo, J. E.
Format: Preprint
Publié: 2024
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author Feng, Shui
Paguyo, J. E.
author_facet Feng, Shui
Paguyo, J. E.
contents The hierarchical Dirichlet process is a discrete random measure used as a prior in Bayesian nonparametrics and motivated by the study of groups of clustered data. We study the asymptotic behavior of the power sum symmetric polynomials for the vector of weights of the hierarchical Dirichlet process as the concentration parameters tend to infinity. We establish central limit theorems and obtain explicit representations for the asymptotic variances, with the latter clearly showing the impact of the hierarchical structure. These objects are related to the homozygosity in population genetics, the Simpson diversity index in ecology, and the Herfindahl-Hirschman index in economics.
format Preprint
id arxiv_https___arxiv_org_abs_2404_16034
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Central limit theorems associated with the hierarchical Dirichlet process
Feng, Shui
Paguyo, J. E.
Probability
60G57, 62F15
The hierarchical Dirichlet process is a discrete random measure used as a prior in Bayesian nonparametrics and motivated by the study of groups of clustered data. We study the asymptotic behavior of the power sum symmetric polynomials for the vector of weights of the hierarchical Dirichlet process as the concentration parameters tend to infinity. We establish central limit theorems and obtain explicit representations for the asymptotic variances, with the latter clearly showing the impact of the hierarchical structure. These objects are related to the homozygosity in population genetics, the Simpson diversity index in ecology, and the Herfindahl-Hirschman index in economics.
title Central limit theorems associated with the hierarchical Dirichlet process
topic Probability
60G57, 62F15
url https://arxiv.org/abs/2404.16034