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On solving stochastic differential equations. / Ermakov, Sergej M. ; Pogosian, Anna A. .

в: Monte Carlo Methods and Applications, Том 25, № 2, 01.06.2019, стр. 155-161.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Ermakov, SM & Pogosian, AA 2019, 'On solving stochastic differential equations', Monte Carlo Methods and Applications, Том. 25, № 2, стр. 155-161. https://doi.org/10.1515/mcma-2019-2038

APA

Ermakov, S. M., & Pogosian, A. A. (2019). On solving stochastic differential equations. Monte Carlo Methods and Applications, 25(2), 155-161. https://doi.org/10.1515/mcma-2019-2038

Vancouver

Ermakov SM, Pogosian AA. On solving stochastic differential equations. Monte Carlo Methods and Applications. 2019 Июнь 1;25(2):155-161. https://doi.org/10.1515/mcma-2019-2038

Author

Ermakov, Sergej M. ; Pogosian, Anna A. . / On solving stochastic differential equations. в: Monte Carlo Methods and Applications. 2019 ; Том 25, № 2. стр. 155-161.

BibTeX

@article{be04845deb3d452a9f1a62bfc40816be,
title = "On solving stochastic differential equations",
abstract = "This paper proposes a new approach to solving Ito stochastic differential equations. It is based on the well-known Monte Carlo methods for solving integral equations (Neumann–Ulam scheme, Markov chain Monte Carlo). The estimates of the solution for a wide class of equations do not have a bias, which distinguishes them from estimates based on difference approximations (Euler, Milstein methods, etc.).",
keywords = "Monte Carlo methods, Markov chain Monte Carlo, stochastic differential equations, Markov chain Monte Carlo, Monte Carlo methods, stochastic differential equations",
author = "Ermakov, {Sergej M.} and Pogosian, {Anna A.}",
year = "2019",
month = jun,
day = "1",
doi = "10.1515/mcma-2019-2038",
language = "English",
volume = "25",
pages = "155--161",
journal = "Monte Carlo Methods and Applications",
issn = "0929-9629",
publisher = "De Gruyter",
number = "2",

}

RIS

TY - JOUR

T1 - On solving stochastic differential equations

AU - Ermakov, Sergej M.

AU - Pogosian, Anna A.

PY - 2019/6/1

Y1 - 2019/6/1

N2 - This paper proposes a new approach to solving Ito stochastic differential equations. It is based on the well-known Monte Carlo methods for solving integral equations (Neumann–Ulam scheme, Markov chain Monte Carlo). The estimates of the solution for a wide class of equations do not have a bias, which distinguishes them from estimates based on difference approximations (Euler, Milstein methods, etc.).

AB - This paper proposes a new approach to solving Ito stochastic differential equations. It is based on the well-known Monte Carlo methods for solving integral equations (Neumann–Ulam scheme, Markov chain Monte Carlo). The estimates of the solution for a wide class of equations do not have a bias, which distinguishes them from estimates based on difference approximations (Euler, Milstein methods, etc.).

KW - Monte Carlo methods

KW - Markov chain Monte Carlo

KW - stochastic differential equations

KW - Markov chain Monte Carlo

KW - Monte Carlo methods

KW - stochastic differential equations

UR - http://www.scopus.com/inward/record.url?scp=85065960792&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/solving-stochastic-differential-equations

U2 - 10.1515/mcma-2019-2038

DO - 10.1515/mcma-2019-2038

M3 - Article

VL - 25

SP - 155

EP - 161

JO - Monte Carlo Methods and Applications

JF - Monte Carlo Methods and Applications

SN - 0929-9629

IS - 2

ER -

ID: 42905698