Abstract
We propose a full discretization to approximate the invariant measure numerically for parabolic stochastic partial differential equations (SPDEs) with non-globally Lipschitz coefficients. We present a priori estimates and regularity estimates of the numerical solution via a variational approach and Malliavin calculus. Under certain hypotheses, we present the time-independent regularity estimates for the corresponding Kolmogorov equation and the time-independent weak convergence analysis for the full discretization. Furthermore, we show that the V-uniformly ergodic invariant measure of the original system is approximated by this full discretization with weak convergence rate. Numerical experiments verify theoretical findings.
Original language | English |
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Pages (from-to) | 55-93 |
Number of pages | 39 |
Journal | Stochastic Processes and their Applications |
Volume | 134 |
DOIs | |
Publication status | Published - Apr 2021 |
Externally published | Yes |
Keywords
- Invariant measure
- Kolmogorov equation
- Malliavin calculus
- Weak convergence
ASJC Scopus subject areas
- Statistics and Probability
- Modelling and Simulation
- Applied Mathematics