Spontaneous clustering in Markov chains. III.~Monte Carlo Algorithms
Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory, Proceedings of the International Conference «Classical and Modern Geometry» dedicated to the 100th anniversary of the birth of Professor Levon Sergeyevich Atanasyan (July 15, 1921—July 5, 1998). Moscow, November 1–4, 2021. Part 3, Tome 222 (2023), pp. 115-133.

Voir la notice de l'article provenant de la source Math-Net.Ru

The third (final) part of the review on the modeling of spontaneous clustering of correlated point sets based on the statistics of nodes of Markov chains. Dedicated to the computational aspects of this problem, it contains a brief introduction into the method of statistical modeling (Monte Carlo method) and a detailed presentation of the specifics of its application to the problem under consideration, including solving the Ornstein-Zernike equation with the Levy-Feldheim stable kernel. The necessary information from the theory of non-Gaussian stable distributions is given, an algorithm for modeling 3-dimensional vectors with a symmetric stable distribution is described, its justification is given, accompanied by graphical and tabular material. In conclusion, the test results are presented. The first part of this work: Itogi Nauki i Tekhniki. Sovremennaya Matematika i Ee Prilozheniya. Tematicheskie Obzory. — 2023. — 220. — P. 125–144. The second part of this work: Itogi Nauki i Tekhniki. Sovremennaya Matematika i Ee Prilozheniya. Tematicheskie Obzory. — 2023. — 221. — P. 128–147.
Keywords: cumulative distribution function, inverse functions, rejection method, statistical weight, characteristic functions, Levy-stable density, functionals, approximating, testing.
@article{INTO_2023_222_a10,
     author = {V. V. Uchaikin and E. V. Kozhemyakina},
     title = {Spontaneous clustering in {Markov} chains. {III.~Monte} {Carlo} {Algorithms}},
     journal = {Itogi nauki i tehniki. Sovremenna\^a matematika i e\"e prilo\v{z}eni\^a. Temati\v{c}eskie obzory},
     pages = {115--133},
     publisher = {mathdoc},
     volume = {222},
     year = {2023},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/INTO_2023_222_a10/}
}
TY  - JOUR
AU  - V. V. Uchaikin
AU  - E. V. Kozhemyakina
TI  - Spontaneous clustering in Markov chains. III.~Monte Carlo Algorithms
JO  - Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory
PY  - 2023
SP  - 115
EP  - 133
VL  - 222
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/INTO_2023_222_a10/
LA  - ru
ID  - INTO_2023_222_a10
ER  - 
%0 Journal Article
%A V. V. Uchaikin
%A E. V. Kozhemyakina
%T Spontaneous clustering in Markov chains. III.~Monte Carlo Algorithms
%J Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory
%D 2023
%P 115-133
%V 222
%I mathdoc
%U http://geodesic.mathdoc.fr/item/INTO_2023_222_a10/
%G ru
%F INTO_2023_222_a10
V. V. Uchaikin; E. V. Kozhemyakina. Spontaneous clustering in Markov chains. III.~Monte Carlo Algorithms. Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory, Proceedings of the International Conference «Classical and Modern Geometry» dedicated to the 100th anniversary of the birth of Professor Levon Sergeyevich Atanasyan (July 15, 1921—July 5, 1998). Moscow, November 1–4, 2021. Part 3, Tome 222 (2023), pp. 115-133. http://geodesic.mathdoc.fr/item/INTO_2023_222_a10/

[1] Zolotarev V. M., Odnomernye ustoichivye raspredeleniya, Nauka, M., 1983

[2] Lappa A. V., Kolchuzhkin A. M., Uchaikin V. V., “Integralnye uravneniya dlya veroyatnostnykh kharakteristik funktsionalov, zadannykh na traektoriyakh markovskoi tsepi”, Metody Monte-Karlo v vychislitelnoi matematike i matematicheskoi fizike, eds. Marchuk G. I., Novosibirsk, 1974, 114–121

[3] Uchaikin V. V., “Spontannaya klasterizatsiya v markovskikh tsepyakh I. Fraktalnaya pyl”, Itogi nauki tekhn. Sovr. mat. prilozh. Temat. obzory., 220 (2023), 125–144

[4] Uchaikin V. V., “Spontannaya klasterizatsiya v markovskikh tsepyakh II. Mezofraktalnaya model”, Itogi nauki tekhn. Sovr. mat. prilozh. Temat. obzory., 221 (2023), 128–147

[5] Uchaikin V. V., Korobko D. A., Gismyatov I. F., “Modifitsirovannyi algoritm Mandelbrota stokhasticheskogo modelirovaniya raspredeleniya galaktik fraktalnogo tipa”, Izv. vuzov. Fiz., 8 (1997), 7–13

[6] Shanks T., “Discriminating between models of galaxy clustering by statistical measures”, Month. Not. Roy. Astron. Soc., 186 (1979), 583–602

[7] Uchaikin V. V., “If the universe were a Levy–Mandelbrot fractal”, Gravit. Cosmology., 10 (2004), 5–24

[8] Uchaikin V. V., “The mesofractal Universe driven by Rayleigh–Levy walks”, Gen. Rel. Gravit., 36:7 (2004), 1689–1717

[9] Uchaikin V. V., “Statistical mechanics of fragmentation-advection processes and monlinear measurements problem, I”, Discont. Nonlin. Complex., 1:1 (2012), 79–112

[10] Uchaikin V. V., “Statistical mechanics of fragmentation-advection processes and monlinear measurements problem, II”, Discont. Nonlin. Complex., 1:2 (2012), 171–196

[11] Uchaikin V. V., Gusarov G. G., “Levy flight applied to random media problems”, J. Math. Phys., 38 (1997), 2453–2464

[12] Uchaikin V. V., Kozhemyakin I. I., “A mesofractal model of interstellar cloudiness”, Universe., 8:5 (2022), 249–262

[13] Uchaikin V. V., Litvinov V. A., Kozhemyakina E. V., Kozhemyakin I. I., “A random walk model for spatial galaxy distribution”, Mathematics., 9:1 (2021), 1-17

[14] Uchaikin V. V., Zolotarev V. M., Chance and Stability. Stable Distributions and Their Applications, VSP, Utrecht, The Netherlands, 1999