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Solving approximately a prediction problem for stochastic jump-diffusion systems. / Averina, T. A.; Rybakov, K. A.

In: Numerical Analysis and Applications, Vol. 10, No. 1, 01.01.2017, p. 1-10.

Research output: Contribution to journal › Article › peer-review

Harvard

Averina, TA & Rybakov, KA 2017, 'Solving approximately a prediction problem for stochastic jump-diffusion systems', Numerical Analysis and Applications, vol. 10, no. 1, pp. 1-10. https://doi.org/10.1134/S1995423917010013

APA

Averina, T. A., & Rybakov, K. A. (2017). Solving approximately a prediction problem for stochastic jump-diffusion systems. Numerical Analysis and Applications, 10(1), 1-10. https://doi.org/10.1134/S1995423917010013

Vancouver

Averina TA, Rybakov KA. Solving approximately a prediction problem for stochastic jump-diffusion systems. Numerical Analysis and Applications. 2017 Jan 1;10(1):1-10. doi: 10.1134/S1995423917010013

Author

Averina, T. A. ; Rybakov, K. A. / Solving approximately a prediction problem for stochastic jump-diffusion systems. In: Numerical Analysis and Applications. 2017 ; Vol. 10, No. 1. pp. 1-10.

BibTeX

@article{b96cf7bbca00410ba5db704731f1aadb,
title = "Solving approximately a prediction problem for stochastic jump-diffusion systems",
abstract = "In this paper, a new approach to solving a prediction problem for nonlinear stochastic differential systems with a Poisson component is discussed. In this approach, the prediction problem is reduced to an analysis of stochastic jump-diffusion systems with terminating and branching paths. The prediction problem can be approximately solved by using numerical methods for stochastic differential equations and methods for modeling inhomogeneous Poisson flows.",
keywords = "branching processes, conditional density, Duncan–Mortensen–Zakai equation, Kolmogorov–Feller equation, Monte Carlo method, optimal filtering problem, prediction problem, stochastic jump-diffusion system, Duncan-Mortensen-Zakai equation, Kolmogorov-Feller equation",
author = "Averina, {T. A.} and Rybakov, {K. A.}",
year = "2017",
month = jan,
day = "1",
doi = "10.1134/S1995423917010013",
language = "English",
volume = "10",
pages = "1--10",
journal = "Numerical Analysis and Applications",
issn = "1995-4239",
publisher = "Maik Nauka-Interperiodica Publishing",
number = "1",

}

RIS

TY - JOUR

T1 - Solving approximately a prediction problem for stochastic jump-diffusion systems

AU - Averina, T. A.

AU - Rybakov, K. A.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - In this paper, a new approach to solving a prediction problem for nonlinear stochastic differential systems with a Poisson component is discussed. In this approach, the prediction problem is reduced to an analysis of stochastic jump-diffusion systems with terminating and branching paths. The prediction problem can be approximately solved by using numerical methods for stochastic differential equations and methods for modeling inhomogeneous Poisson flows.

AB - In this paper, a new approach to solving a prediction problem for nonlinear stochastic differential systems with a Poisson component is discussed. In this approach, the prediction problem is reduced to an analysis of stochastic jump-diffusion systems with terminating and branching paths. The prediction problem can be approximately solved by using numerical methods for stochastic differential equations and methods for modeling inhomogeneous Poisson flows.

KW - branching processes

KW - conditional density

KW - Duncan–Mortensen–Zakai equation

KW - Kolmogorov–Feller equation

KW - Monte Carlo method

KW - optimal filtering problem

KW - prediction problem

KW - stochastic jump-diffusion system

KW - Duncan-Mortensen-Zakai equation

KW - Kolmogorov-Feller equation

UR - http://www.scopus.com/inward/record.url?scp=85014759672&partnerID=8YFLogxK

U2 - 10.1134/S1995423917010013

DO - 10.1134/S1995423917010013

M3 - Article

AN - SCOPUS:85014759672

VL - 10

SP - 1

EP - 10

JO - Numerical Analysis and Applications

JF - Numerical Analysis and Applications

SN - 1995-4239

IS - 1

ER -

ID: 8968023