Hostname: page-component-7b7567c8c-tnzcf Total loading time: 0 Render date: 2026-11-14T11:22:12.211Z Has data issue: false hasContentIssue false

Asymptotics of poisson approximation to random discrete distributions: an analytic approach

Published online by Cambridge University Press:  01 July 2016

Hsien-Kuei Hwang*
Affiliation:
Academia Sinica
*
∗ Postal address: Institute of Statistical Science, Academia Sinica, Taipei 115, Taiwan. Email address: hkhwang@stat.sinica.edu.tw

Abstract

A general analytic scheme for Poisson approximation to discrete distributions is studied in which the asymptotic behaviours of the generalized total variation, Fortet-Mourier (or Wasserstein), Kolmogorov and Matusita (or Hellinger) distances are explicitly characterized. Applications of this result include many number-theoretic functions and combinatorial structures. Our approach differs from most of the existing ones in the literature and is easily amended for other discrete approximations; arithmetic and combinatorial examples for Bessel approximation are also presented. A unified approach is developed for deriving uniform estimates for probability generating functions of the number of components in general decomposable combinatorial structures, with or without analytic continuation outside their circles of convergence.

Information

Type
General Applied Probability
Copyright
Copyright © Applied Probability Trust 1999 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable