Skip to content
DraconiticResearch
Search Sources API
181,686 studies31 sourcesUpdated 14 min ago
PreprintarXiv licencearXiv

Stein's method for negative binomial and hyper-negative-binomial laws, with applications

Abstract

We develop Stein's method for the negative binomial law and for the hyper-negative-binomial law, the law of the smallest row total of an array of independent geometric variables given the differences of the row totals, with every constant explicit. The main instrument is a comparison of two biasings of the approximated variable, which cancels the rate term exactly at the matched parameter. We provide total variation bounds for sums of independent geometric variables at drifting parameters, for sums of dependent geometric variables (the Arratia-Goldstein-Gordon theorem with geometric summands and the Poisson law as an endpoint), and for Poisson mixtures; the exact conditional law of negative-binomial counts given their differences, with the Bessel law as its Poisson limit; and a dependency expansion for the column direction of a contingency table. A final section verifies every bound numerically, with one script per result.

Related

  1. Negative-binomial ensemble filtering for discrete-time Hawkes network reconstruction
    Naratip Santitissadeekorn
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
  2. A spatiotemporal negative binomial model with dynamic dispersion: An application to Tuberculosis infections
    Rodrigo B. Silva, Luiza S. C. Piancastelli, Wagner Barreto-Souza
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
  3. Reference-based sensitivity analysis for repeated count outcomes using negative binomial margins and a Gaussian copula
    Divan Aristo Burger, Emmanuel Lesaffre, Reynaldo Martina
    arXivPreprintarXiv licenceFull textStatisticsarXiv
  4. Regularity and depth of binomial ideals arising from combinatorics
    Takayuki Hibi, Seyed Amin Seyed Fakhari
    arXivPreprintarXiv licenceFull textAlgebra & number theoryCombinatorics & discrete mathematicsarXiv
  5. Diagonal F-threshold of binomial edge ideals
    Giancarlo Rinaldo, Francesco Romeo
    arXivPreprintCC0Full textAlgebra & number theoryCombinatorics & discrete mathematicsarXiv
BibTeX
@misc{desalvo2026steins,
  title = {{Stein's method for negative binomial and hyper-negative-binomial laws, with applications}},
  author = {Stephen DeSalvo},
  howpublished = {arXiv},
  year = {2026},
  month = nov,
  doi = {10.48550/arxiv.2611.00275},
  eprint = {2611.00275},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2611.00275},
}
RIS
TY  - UNPB
TI  - Stein's method for negative binomial and hyper-negative-binomial laws, with applications
AU  - Stephen DeSalvo
PY  - 2026
DA  - 2026/11/01
PB  - arXiv
DO  - 10.48550/arxiv.2611.00275
UR  - https://arxiv.org/abs/2611.00275
AB  - We develop Stein's method for the negative binomial law and for the hyper-negative-binomial law, the law of the smallest row total of an array of independent geometric variables given the differences of the row totals, with every constant explicit. The main instrument is a comparison of two biasings of the approximated variable, which cancels the rate term exactly at the matched parameter. We provide total variation bounds for sums of independent geometric variables at drifting parameters, for sums of dependent geometric variables (the Arratia-Goldstein-Gordon theorem with geometric summands and the Poisson law as an endpoint), and for Poisson mixtures; the exact conditional law of negative-binomial counts given their differences, with the Bessel law as its Poisson limit; and a dependency expansion for the column direction of a contingency table. A final section verifies every bound numerically, with one script per result.
ER  -