Numerical stationary distribution and its convergence for nonlinear stochastic differential equations

Liu, Wei and Mao, Xuerong (2015) Numerical stationary distribution and its convergence for nonlinear stochastic differential equations. Journal of Computational and Applied Mathematics, 276. pp. 16-29. ISSN 0377-0427 (https://doi.org/10.1016/j.cam.2014.08.019)

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Abstract

To avoid finding the stationary distributions of stochastic differential equations by solving the nontrivial Kolmogorov-Fokker-Planck equations, the numerical stationary distributions are used as the approximations instead. This paper is devoted to approximate the stationary distribution of the underlying equation by the Backward Euler-Maruyama method. Currently existing results [21, 31, 33] are extended in this paper to cover larger range of nonlinear SDEs when the linear growth condition on the drift coeffcient is violated.

ORCID iDs

Mao, Xuerong ORCID: https://orcid.org/0000-0002-6768-9864

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• Item metadata

  Item type:	Article
  ID code:	49943
  Dates:	Date Event 1 March 2015 Published 27 August 2014 Published Online 19 August 2014 Accepted
  Notes:	. NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Computational and Applied Mathematics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Computational and Applied Mathematics, [VOL 276 (01/03/15] DOI: 10.1016/j.cam.2014.08.019
  Subjects:	Science > Mathematics > Probabilities. Mathematical statistics
  Department:	Faculty of Science > Mathematics and Statistics
  Depositing user:	Pure Administrator
  Date deposited:	21 Oct 2014 10:34
  Last modified:	11 Nov 2024 10:49
  Related URLs:	Journal or Publication
  URI:	https://strathprints.strath.ac.uk/id/eprint/49943