On moderate deviations in Poisson approximation
arXiv:1906.10016 · doi:10.1017/jpr.2020.47
Abstract
In this paper, we first use the distribution of the number of records to demonstrate that the right tail probabilities of counts of rare events are generally better approximated by the right tail probabilities of Poisson distribution than {those} of normal distribution. We then show the moderate deviations in Poisson approximation generally require an adjustment and, with suitable adjustment, we establish better error estimates of the moderate deviations in Poisson approximation than those in \cite{CFS}. Our estimates contain no unspecified constants and are easy to apply. We illustrate the use of the theorems in six applications: Poisson-binomial distribution, matching problem, occupancy problem, birthday problem, random graphs and 2-runs. The paper complements the works of \cite{CC92,BCC95,CFS}.
arXiv comment29 pages and 5 figures
References in corpus (7)
- Normal approximation under local dependence
- Translated Poisson approximation using exchangeable pair couplings
- Exchangeable pairs and Poisson approximation
- From Stein identities to moderate deviations
- Size bias, sampling, the waiting time paradox, and infinite divisibility: when is the increment independent?
- Zero biasing and a discrete central limit theorem
- Relative Error of Scaled Poisson Approximation via Stein's Method