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High Order Numerical Approximation of the Invariant Measure of Ergodic SDEs

Published inSIAM journal on numerical analysis, vol. 52, no. 4, p. 1600-1622
Publication date2014
Abstract

We introduce new sufficient conditions for a numerical method to approximate with high order of accuracy the invariant measure of an ergodic system of stochastic differential equations, independently of the weak order of accuracy of the method. We then present a systematic procedure based on the framework of modified differential equations for the construction of stochastic integrators that capture the invariant measure of a wide class of ergodic SDEs (Brownian and Langevin dynamics) with an accuracy independent of the weak order of the underlying method. Numerical experiments confirm our theoretical findings.

Keywords
  • Stochastic differential equations
  • Weak convergence
  • Modified differential equations
  • Backward error analysis
  • Invariant measure
  • Ergodicity
Research groups
Funding
  • Swiss National Science Foundation - 200020 144313/1
Citation (ISO format)
ABDULLE, Assyr, VILMART, Gilles, ZYGALAKIS, Konstantinos C. High Order Numerical Approximation of the Invariant Measure of Ergodic SDEs. In: SIAM journal on numerical analysis, 2014, vol. 52, n° 4, p. 1600–1622. doi: 10.1137/130935616
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Article (Accepted version)
accessLevelPublic
Identifiers
Journal ISSN0036-1429
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Technical informations

Creation11/12/2014 3:46:00 PM
First validation11/12/2014 3:46:00 PM
Update time03/14/2023 10:15:21 PM
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