On the modeling of stationary sequences using the inverse distribution function Full article
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Сибирские электронные математические известия (Siberian Electronic Mathematical Reports)
, E-ISSN: 1813-3304 |
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| Output data | Year: 2022, Volume: 19, Number: 2, Pages: 502-516 Pages count : 15 DOI: 10.33048/semi.2022.19.042 | ||
| Tags | modeling of stationary processes, long-range dependence, limit theorems, function words in fiction. | ||
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Abstract:
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
Cite:
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
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
Dates:
| Submitted: | Sep 20, 2021 |
| Published online: | Aug 23, 2022 |
| Published print: | Mar 7, 2023 |
Identifiers:
| Web of science: | WOS:000886649600008 |
| Scopus: | 2-s2.0-85136709944 |
| Elibrary: | 50336828 |
Citing:
| DB | Citing |
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| Scopus | 1 |