Journal article
On moderate deviations in Poisson approximation
Qingwei Liu, Aihua Xia
JOURNAL OF APPLIED PROBABILITY | CAMBRIDGE UNIV PRESS | Published : 2020
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 a Poisson distribution than those of the normal distribution. We then show that 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 [18]. Our estimates contain no unspecified constants and are easy to apply. We illustrate the use of the theorems via six applications: Poisson-binomial distribution, the matching problem, the o..
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Awarded by Australian Research Council
Funding Acknowledgements
We thank the anonymous referees for suggesting the 'naive bound' in Remark 2.1 and for comments leading to the improved version of the paper. We also thank Serguei Novak for email discussions about the quality of the bounds presented in the paper versus the `naive bound'. This work was supported in part by the Chinese Scholarship Council and in part by Australian Research Council grant DP190100613.