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Poissonization Principle for a Class of Additive Statistics Научная публикация

Журнал Mathematics
, E-ISSN: 2227-7390
Вых. Данные Год: 2022, Том: 10, Номер: 21, Номер статьи : 4084, Страниц : DOI: 10.3390/math10214084
Ключевые слова additive functional; empirical point process; group frequency; Poisson point process; Poissonization
Авторы Borisov I. 1,2 , Jetpisbaev M. 1,2
Организации
1 Laboratory of Probability Theory and Mathematical Statistics, Sobolev Institute of Mathematics, Novosibirsk, 630090, Russian Federation
2 Novosibirsk State University, Novosibirsk, 630090, Russian Federation

Информация о финансировании (1)

1 Российский научный фонд 22-21-00414

Реферат: In this paper, we consider a class of additive functionals of a finite or countable collection of the group frequencies of an empirical point process that corresponds to, at most, a countable partition of the sample space. Under broad conditions, it is shown that the asymptotic behavior of the distributions of such functionals is similar to the behavior of the distributions of the same functionals of the accompanying Poisson point process. However, the Poisson versions of the additive functionals under consideration, unlike the original ones, have the structure of sums (finite or infinite) of independent random variables that allows us to reduce the asymptotic analysis of the distributions of additive functionals of an empirical point process to classical problems of the theory of summation of independent random variables. © 2022 by the authors.
Библиографическая ссылка: Borisov I. , Jetpisbaev M.
Poissonization Principle for a Class of Additive Statistics
Mathematics. 2022. V.10. N21. 4084 . DOI: 10.3390/math10214084 WOS Scopus РИНЦ OpenAlex
Даты:
Поступила в редакцию: 5 сент. 2022 г.
Принята к публикации: 29 окт. 2022 г.
Опубликована в печати: 2 нояб. 2022 г.
Опубликована online: 2 нояб. 2022 г.
Идентификаторы БД:
Web of science: WOS:000884545700001
Scopus: 2-s2.0-85141876805
РИНЦ: 57508806
OpenAlex: W4309090453
Цитирование в БД:
БД Цитирований
Scopus 2
Web of science 2
OpenAlex 3
Альметрики: