Geodesic
On the modeling of stationary sequences using the inverse distribution function
Sibirskie èlektronnye matematičeskie izvestiâ, Tome 19 (2022) no. 2, pp. 502-516

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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.
Keywords: modeling of stationary processes, long-range dependence, limit theorems, function words in fiction. 
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     author = {N. S. Arkashov},
     title = {On the modeling of stationary sequences using the inverse distribution function},
     journal = {Sibirskie \`elektronnye matemati\v{c}eskie izvesti\^a},
     pages = {502--516},
     publisher = {mathdoc},
     volume = {19},
     number = {2},
     year = {2022},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/SEMR_2022_19_2_a17/}
}
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N. S. Arkashov. On the modeling of stationary sequences using the inverse distribution function. Sibirskie èlektronnye matematičeskie izvestiâ, Tome 19 (2022) no. 2, pp. 502-516. http://geodesic.mathdoc.fr/item/SEMR_2022_19_2_a17/