Abstract
Abstract
In this paper, we show that the abstract framework developed in
[G. Pagès and C. Rey, Recursive computation of the invariant distribution of Markov and Feller processes, preprint 2017, https://arxiv.org/abs/1703.04557]
and inspired by
[D. Lamberton and G. Pagès,
Recursive computation of the invariant distribution of a diffusion,
Bernoulli 8 2002, 3, 367–405]
can be used to build invariant distributions for Brownian diffusion processes using the Milstein scheme and for diffusion processes with censored jump using the Euler scheme. Both studies rely on a weakly mean-reverting setting for both cases. For the Milstein scheme we prove the convergence for test functions with polynomial (Wasserstein convergence) and exponential growth. For the Euler scheme of diffusion processes with censored jump we prove the convergence for test functions with polynomial growth.
Subject
Applied Mathematics,Statistics and Probability
Reference52 articles.
1. Weak approximation of solutions of systems of stochastic differential equations;Numerical Integration of Stochastic Differential Equations,1995
2. Recursive computation of the invariant distribution of a diffusion;Bernoulli,2002
3. Ergodic approximation of the distribution of a stationary diffusion: Rate of convergence;Ann. Appl. Probab.,2012
4. Weak convergence of recursions;Stochastic Process. Appl.,1997
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