关于泊松逼近

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY Journal of Theoretical Probability Pub Date : 2024-02-28 DOI:10.1007/s10959-023-01310-4
S. Y. Novak
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引用次数: 0

摘要

在过去的六十年里,对独立整数值随机变量之和的分布进行泊松近似的精度评估问题引起了广泛关注。普罗霍罗夫、科尔莫戈罗夫、勒卡姆、肖金、巴尔博、霍尔、德赫维尔斯、普菲弗、罗斯等人都对这一课题做出了贡献。从实践角度看,该问题在保险、可靠性理论、极值理论等方面都有重要应用。从理论角度看,该课题为科尔莫戈罗夫关于用无限可分定律逼近独立随机变量之和的分布的准确性问题提供了启示。数十年来,人们一直在探索如何用一个正确的(尽可能好的)常数来估计泊松近似的精度。我们提出了在用点度量评估近似精度的情况下该问题的解决方案。我们对前人建立的相应不等式进行了概括和锐化。对于整数值r.v.s.之和分布的复合泊松近似这一深入研究的课题,我们建立了一个新的结果。
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On Poisson Approximation

The problem of evaluating the accuracy of Poisson approximation to the distribution of a sum of independent integer-valued random variables has attracted a lot of attention in the past six decades. Among authors who contributed to the topic are Prokhorov, Kolmogorov, LeCam, Shorgin, Barbour, Hall, Deheuvels, Pfeifer, Roos, and many others. From a practical point of view, the problem has important applications in insurance, reliability theory, extreme value theory, etc. From a theoretical point of view, the topic provides insights into Kolmogorov’s problem concerning the accuracy of approximation of the distribution of a sum of independent random variables by infinitely divisible laws. The task of establishing an estimate of the accuracy of Poisson approximation with a correct (the best possible) constant at the leading term remained open for decades. We present a solution to that problem in the case where the accuracy of approximation is evaluated in terms of the point metric. We generalise and sharpen the corresponding inequalities established by preceding authors. A new result is established for the intensively studied topic of compound Poisson approximation to the distribution of a sum of integer-valued r.v.s.

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来源期刊
Journal of Theoretical Probability
Journal of Theoretical Probability 数学-统计学与概率论
CiteScore
1.50
自引率
12.50%
发文量
65
审稿时长
6-12 weeks
期刊介绍: Journal of Theoretical Probability publishes high-quality, original papers in all areas of probability theory, including probability on semigroups, groups, vector spaces, other abstract structures, and random matrices. This multidisciplinary quarterly provides mathematicians and researchers in physics, engineering, statistics, financial mathematics, and computer science with a peer-reviewed forum for the exchange of vital ideas in the field of theoretical probability.
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