Numerical method for stationary distribution of stochastic differential equations with Markovian switching
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摘要
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.
论文关键词：Brownian motion,Stationary distribution,Lipschitz condition,Markov chain,Stochastic differential equations,Euler–Maruyama methods,Weak convergence to stationary measures
论文评审过程：Received 23 September 2003, Revised 18 February 2004, Available online 25 May 2004.
论文官网地址：https://doi.org/10.1016/j.cam.2004.03.016
