English

Persistence exponents via perturbation theory: AR(1)-processes

Probability 2019-10-23 v2 Functional Analysis

Abstract

For AR(1)-processes Xn=ρXn1+ξnX_n=\rho X_{n-1}+\xi_n, nNn\in\mathbb{N}, where ρR\rho\in\mathbb{R} and (ξi)iN(\xi_i)_{i\in\mathbb{N}} is an i.i.d. sequence of random variables, we study the persistence probabilities P(X00,,XN0)\mathbb{P}(X_0\ge 0,\dots, X_N\ge 0) for NN\to\infty. 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 ρ\rho for normally distributed AR(1)-processes.

Keywords

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

R2 v1 2026-06-23T04:49:50.357Z