Stein factors for negative binomial approximation in Wasserstein distance

A. D. Barbour, H. L. Gan, A. Xia

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The paper gives the bounds on the solutions to a Stein equation for the negative binomial distribution that are needed for approximation in terms of the Wasserstein metric. The proofs are probabilistic, and follow the approach introduced in Barbour and Xia (Bernoulli 12 (2006) 943-954). The bounds are used to quantify the accuracy of negative binomial approximation to parasite counts in hosts. Since the infectivity of a population can be expected to be proportional to its total parasite burden, the Wasserstein metric is the appropriate choice.

Original languageEnglish (US)
Pages (from-to)1002-1013
Number of pages12
JournalBernoulli
Volume21
Issue number2
DOIs
StatePublished - May 1 2015

Keywords

  • Negative binomial approximation
  • Stein factors
  • Stein's method
  • Wasserstein distance

ASJC Scopus subject areas

  • Statistics and Probability

Fingerprint Dive into the research topics of 'Stein factors for negative binomial approximation in Wasserstein distance'. Together they form a unique fingerprint.

Cite this