Persistence exponents via perturbation theory: AR(1)-processes
Probability
2019-10-23 v2 Functional Analysis
Abstract
For AR(1)-processes , , where and is an i.i.d. sequence of random variables, we study the persistence probabilities for . For a wide class of Markov processes a recent result [Aurzada, Mukherjee, Zeitouni; arXiv:1703.06447; 2017] shows that these probabilities decrease exponentially fast and that the rate of decay can be identified as an eigenvalue of some integral operator. We discuss a perturbation technique to determine a series expansion of the eigenvalue in the parameter for normally distributed AR(1)-processes.
Cite
@article{arxiv.1810.09861,
title = {Persistence exponents via perturbation theory: AR(1)-processes},
author = {Frank Aurzada and Marvin Kettner},
journal= {arXiv preprint arXiv:1810.09861},
year = {2019}
}
Comments
Version 2 contains an appendix that develops the relevant concepts from perturbation theory for linear operators