Infinitely resizable urn models

Abstract Any margin of the multinomial distribution is multinomially distributed. Retaining this closure property, a family of generalized multinomial distributions is proposed. This family is characterized within multiplicative probability measures, using the Bell polynomial. The retained closure property simplifies marginal properties such as moments. The family can be obtained by conditioning independent infinitely divisible distributions on the total and also by mixing the multinomial distribution with the normalized infinitely divisible distribution. The closure property justifies a stochastic process of the family by Kolmogorov’s extension theorem. Over time, Gibbs partitions of a positive integer appear as the limiting distributions of the family.

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Publication Details

Journal
Journal of Applied Probability
Published
2025-11-24
DOI
https://doi.org/10.1017/jpr.2025.10042
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
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article

Infinitely resizable urn models

Nobuaki Hoshino
Journal of Applied Probability
Random Matrices and Applications
article

Infinitely resizable urn models

Nobuaki Hoshino
article en

Abstract

Abstract Any margin of the multinomial distribution is multinomially distributed. Retaining this closure property, a family of generalized multinomial distributions is proposed. This family is characterized within multiplicative probability measures, using the Bell polynomial. The retained closure property simplifies marginal properties such as moments. The family can be obtained by conditioning independent infinitely divisible distributions on the total and also by mixing the multinomial distribution with the normalized infinitely divisible distribution. The closure property justifies a stochastic process of the family by Kolmogorov’s extension theorem. Over time, Gibbs partitions of a positive integer appear as the limiting distributions of the family.

Journal of Applied Probability
Kanazawa University (JP)
Openalex Percentile: Top 67%
Random Matrices and Applications
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