Random evolutions in Poisson approximation scheme

Authors

  • I. V. Samoilenko Taras Shevchenko National University of Kyiv
  • T. A. Samoilenko National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 37, Prosp. Peremohy, Kyiv, Ukraine, 03056
  • Bogdan V. Dovgai Taras Shevchenko National University of Kyiv

DOI:

https://doi.org/10.17721/1812-5409.2021/2.10

Keywords:

random evolutions, Poisson approximation scheme, large deviations problem

Abstract

The operator approach in the study of random evolutions allows us to obtain the following results in the Poisson approximation scheme: functional limit theorems at increasing time intervals and the solution of the large deviations problem. We will focus on the last task.

To solve the problem, asymptotic analysis of nonlinear generators of random evolutions with Markov switching should be conducted in the series scheme. The specifics of asymptotic analysis is conditioned by the fact that the jump values of the stochastic system are split into two parts: a small jump taking values with probabilities close to one and a big jump taken values with probabilities tending to zero together with the series parameter $\varepsilon\to 0$. So, in the Poisson approximation principle the probabilities (or intensities) of jumps are normalized by the series parameter $\varepsilon >0$.

Having the limit nonlinear generator, we are able to construct the rate functional to solve the large deviations problem.

Pages of the article in the issue: 69 - 77

Language of the article: Ukrainian

References

DUPUIS, P., ELLIS, R.S. (1997) A weak convergence approach to the theory of large deviations. New York: Wiley.

BRYC, W. (1990) Large deviations by the asymptotic value method. Diffusion processes and related problems in analysis. Basel: Birkhauser. pp. 447-472.

FENG, J., KURTZ, T.G. (2006) Large deviation for stochastic processes. Mathematical Surveys and Monographs, 131. Providence, RI, American Mathematical Society.

JACOD, J., SHIRYAEV, A.N. (2003) Limit theorems for stochastic processes. Berlin: Springer-Verlag.

KOROLIUK, V.S., LIMNIOS N. (2005) Stochastic systems in merging phase space. Singapore: World Scientific Publishing Company.

KURTZ, T.G. (1987) Martingale problems for controlled processes. Lecture notes in control and information sciences. Berlin: Springer. Vol.91. pp. 75-90.

NISIO, M. (1976) On a non-linear semi-group attached to stochastic optimal control. Publ. RIMS, Kyoto Univ. No.13. pp. 513-537.

NISIO, M. (1976) On stochastic optimal controls and envelope of Markovian semi-groups. Proc. Intern. Symp. SDE. Kyoto: Kinokuniya. pp.297-325.

KOROLIOUK, D., SAMOILENKO I. (2021) Random evolutionary systems: asymptotic properties and large deviations. London: ISTE-John Wiley and Sons.

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Published

2021-11-04

Issue

Section

Algebra, Geometry and Probability Theory

How to Cite

Samoilenko, I. V., Samoilenko, T. A., & Dovgai, B. V. (2021). Random evolutions in Poisson approximation scheme. Bulletin of Taras Shevchenko National University of Kyiv. Physics and Mathematics, 2, 69-77. https://doi.org/10.17721/1812-5409.2021/2.10