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

X. Mao, C. Yuan, G. Yin

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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.
Original languageEnglish
Pages (from-to)1-27
Number of pages26
JournalJournal of Computational and Applied Mathematics
Issue number1
Publication statusPublished - Feb 2005


  • Brownian motion
  • stationary distribution
  • Lipschitz condition
  • Markov chain
  • stochastic differential equations
  • Euler-Maruyama methods
  • weak convergence to stationary measures

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