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Numerical method for stationary distribution of stochastic differential equations with Markovian switching

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

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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
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
Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 05 Nov 2007
    Last modified: 04 Sep 2014 16:43
    URI: http://strathprints.strath.ac.uk/id/eprint/4589

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