On the modeling of stationary sequences using the inverse distribution function | Sciact - Система учета научной деятельности ИМ СО РАН

On the modeling of stationary sequences using the inverse distribution function Научная публикация

Журнал

Сибирские электронные математические известия (Siberian Electronic Mathematical Reports)
, E-ISSN: 1813-3304

Вых. Данные

Год: 2022, Том: 19, Номер: 2, Страницы: 502-516 Страниц : 15 DOI: 10.33048/semi.2022.19.042

Ключевые слова

modeling of stationary processes, long-range dependence, limit theorems, function words in fiction.

Авторы

Arkashov N.S. ¹

Организации

1	Novosibirsk State Technical, 630073, Russia

We study a method for modeling stationary sequences, which is implemented generally speaking by a nonlinear transformation of Gaussian noise. The paper establishes limit theorems in the metric space D[0,1] for normalized processes of partial sums of sequences obtained as a result of the mentioned Gaussian noise transformation. Application of this method for simulating function words in fiction is investigated

Arkashov N.S.
On the modeling of stationary sequences using the inverse distribution function
Сибирские электронные математические известия (Siberian Electronic Mathematical Reports). 2022. V.19. N2. P.502-516. DOI: 10.33048/semi.2022.19.042 WOS Scopus РИНЦ

Поступила в редакцию:	20 сент. 2021 г.
Опубликована online:	23 авг. 2022 г.
Опубликована в печати:	7 мар. 2023 г.

Web of science:	WOS:000886649600008
Scopus:	2-s2.0-85136709944
РИНЦ:	50336828

БД	Цитирований
Scopus	1