Novel Stein-type Characterizations of Bivariate Count Distributions with Applications

Fuente: arXiv
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Autori principali: Wang, Shaochen, Weiß, Christian H.
Natura: Preprint
Pubblicazione: 2026
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author Wang, Shaochen
Weiß, Christian H.
author_facet Wang, Shaochen
Weiß, Christian H.
contents The derivation and application of Stein identities have received considerable research interest in recent years, especially for continuous or discrete-univariate distributions. In this paper, we complement the existing literature by deriving and investigating Stein-type characterizations for the three most common types of bivariate count distributions, namely the bivariate Poisson, binomial, and negative-binomial distribution. Then, we demonstrate the practical relevance of these novel Stein identities by a couple of applications, namely the deduction of sophisticated moment expressions, of flexible goodness-of-fit tests, and of novel tests for the symmetry of bivariate count distributions. The paper concludes with an analysis of real-world data examples.
format Preprint
id arxiv_https___arxiv_org_abs_2602_23775
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Novel Stein-type Characterizations of Bivariate Count Distributions with Applications
Wang, Shaochen
Weiß, Christian H.
Methodology
60E05, 62F03
The derivation and application of Stein identities have received considerable research interest in recent years, especially for continuous or discrete-univariate distributions. In this paper, we complement the existing literature by deriving and investigating Stein-type characterizations for the three most common types of bivariate count distributions, namely the bivariate Poisson, binomial, and negative-binomial distribution. Then, we demonstrate the practical relevance of these novel Stein identities by a couple of applications, namely the deduction of sophisticated moment expressions, of flexible goodness-of-fit tests, and of novel tests for the symmetry of bivariate count distributions. The paper concludes with an analysis of real-world data examples.
title Novel Stein-type Characterizations of Bivariate Count Distributions with Applications
topic Methodology
60E05, 62F03
url https://arxiv.org/abs/2602.23775