A Donsker theorem to simulate one-dimensional processes with measurable coefficients
Pierre Étoré, Antoine Lejay · ESAIM Probability and Statistics · 2007
In this paper, we prove a Donsker theorem for one-dimensional processes generated by an operator with measurable coefficients. We construct a random walk on any grid on the state space, using the transition probabilities of the approximated process, and the conditional average times it spends on each cell of the grid. Indeed we can compute these quantities by solving some suitable elliptic PDE problems.