Conway--Maxwell multivariate Bernoulli distribution

Fuente: arXiv
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Hauptverfasser: Cossette, Hélène, Marceau, Etienne, Mutti, Alessandro, Semeraro, Patrizia
Format: Preprint
Veröffentlicht: 2026
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author Cossette, Hélène
Marceau, Etienne
Mutti, Alessandro
Semeraro, Patrizia
author_facet Cossette, Hélène
Marceau, Etienne
Mutti, Alessandro
Semeraro, Patrizia
contents We investigate the Conway--Maxwell multivariate Bernoulli distributions, a family of multivariate Bernoulli distributions derived from the Conway--Maxwell-binomial distribution. We show that it is possible to set the parametrization such that the Bernoulli marginals remain intact, allowing us to study dependence properties within this family. In particular, we demonstrate that this family spans the full spectrum of dependence. Moreover, for specific ranges of the parameters, these distributions satisfy the strongly Rayleigh property, a negative dependence notion stronger than negative association.
format Preprint
id arxiv_https___arxiv_org_abs_2604_23367
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Conway--Maxwell multivariate Bernoulli distribution
Cossette, Hélène
Marceau, Etienne
Mutti, Alessandro
Semeraro, Patrizia
Statistics Theory
We investigate the Conway--Maxwell multivariate Bernoulli distributions, a family of multivariate Bernoulli distributions derived from the Conway--Maxwell-binomial distribution. We show that it is possible to set the parametrization such that the Bernoulli marginals remain intact, allowing us to study dependence properties within this family. In particular, we demonstrate that this family spans the full spectrum of dependence. Moreover, for specific ranges of the parameters, these distributions satisfy the strongly Rayleigh property, a negative dependence notion stronger than negative association.
title Conway--Maxwell multivariate Bernoulli distribution
topic Statistics Theory
url https://arxiv.org/abs/2604.23367