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Inhomogeneous functionals and approximations of invariant distributions of ergodic diffusions: Error analysis through central limit theorem and moderate deviation asymptotics

2018/05/16 by Arnab Ganguly, Ganguly, Arnab, P. Sundar +1
Computer Science · Economics, Econometrics and Finance · Mathematics · #60F05 #60F10 #60H10 #60H35 #65C30 #Advanced Mathematical Modeling in Engineering #FOS: Mathematics #Mathematical Biology Tumor Growth #Probability (math.PR) #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1805.06388

openalex publication_date 2018/05/16 · openalex created_date 2018/06/01 · openalex updated_date 2026/07/28

Abstract

The paper considers an Euler discretization based numerical scheme for approximating functionals of invariant distribution of an ergodic diffusion. Convergence of the numerical scheme is shown for suitably chosen discretization step, and a thorough error analysis is conducted by proving central limit theorem and moderate deviation principle for the error term. The paper is a first step in understanding efficiency of discretization based numerical schemes for estimating invariant distributions, which is comparatively much less studied than the schemes used for generating approximate trajectories of diffusions over finite time intervals. The potential applications of these results also extend to other areas including mathematical physics, parameter inference of ergodic diffusions and analysis of multiscale dynamical systems with averaging.

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