Mao, X. and Yuan, C. and Yin, G.
(2005)
*Numerical method for stationary distribution of stochastic differential equations with Markovian switching.*
Journal of Computational and Applied Mathematics, 174 (1).
pp. 1-27.
ISSN 0377-0427

Official URL: http://dx.doi.org/10.1016/j.cam.2004.03.016

## Abstract

In principle, once the existence of the stationary distribution of a stochastic differential equation with Markovian switching is assured, we may compute it by solving the associated system of the coupled Kolmogorov-Fokker-Planck equations. However, this is nontrivial in practice. As a viable alternative, we use the Euler-Maruyama scheme to obtain the stationary distribution in this paper.

Item type: | Article |
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ID code: | 4589 |

Keywords: | Brownian motion, stationary distribution, Lipschitz condition, Markov chain, stochastic differential equations, Euler-Maruyama methods, weak convergence to stationary measures, Probabilities. Mathematical statistics, Computational Mathematics, Applied Mathematics |

Subjects: | Science > Mathematics > Probabilities. Mathematical statistics |

Department: | Faculty of Science > Mathematics and Statistics |

Depositing user: | Strathprints Administrator |

Date Deposited: | 05 Nov 2007 |

Last modified: | 10 Dec 2015 17:11 |

URI: | http://strathprints.strath.ac.uk/id/eprint/4589 |

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