Environment Reconstruction for a Class of Diffusions

Read full text
Authors: Carlos G. Pacheco, Mariana Pérez-Rojas
Cited by: 0
References: 22

Abstract

Abstract We present an algorithm designed to estimate the so-called environment for diffusions driven by a potential. The technique uses observations from a single path to give a non-parametric estimation of the drift coefficient in a stochastic differential equation. We use an ergodic theorem for diffusions developed by K.Itô and H.P.McKean in a straightforward manner. Furthermore, we develop an estimator to approximate the occupation time of the observed path. Subsequently, we asses the algorithm’s effectiveness through simulations. We generate a path of the diffusion along with its associated environment, and then, by applying our algorithm, we compare the resulting environment with the known a priori one. All programming implementations are conducted using MATLAB.

Fields of Study & Subjects

Stochastic processes and financial applications Stochastic processes and statistical mechanics Control Systems and Identification

Publication details

Journal / source
Methodology And Computing In Applied Probability
Volume
28
Issue
1
Publication date
12 January 2026
Language
EN