The Bootstrap for Dynamical Systems
Abstract
Despite their deterministic nature, dynamical systems often exhibit seemingly random behaviour. Consequently, a dynamical system is usually represented by a probabilistic model of which the unknown parameters must be estimated using statistical methods. When measuring the uncertainty of such parameter estimation, the bootstrap stands out as a simple but powerful technique. In this paper, we develop the bootstrap for dynamical systems and establish not only its consistency but also its second-order efficiency via a novel \textit{continuous} Edgeworth expansion for dynamical systems. This is the first time such continuous Edgeworth expansions have been studied. Moreover, we verify the theoretical results about the bootstrap using computer simulations.
Cite
@article{arxiv.2108.08461,
title = {The Bootstrap for Dynamical Systems},
author = {Kasun Fernando and Nan Zou},
journal= {arXiv preprint arXiv:2108.08461},
year = {2021}
}
Comments
51 pages, 4 figures