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 0377-0427Full text not available in this repository. (Request a copy from the Strathclyde author)
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.
|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:||06 Jan 2017 05:54|