Before and beyond the mixing time: New approximations for additive functionals of stationary Gauss-Markov processes

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Bellerino, Gabriele, Rohde, Angelika
Format: Preprint
Published: 2026
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918494428200960
author Bellerino, Gabriele
Rohde, Angelika
author_facet Bellerino, Gabriele
Rohde, Angelika
contents Whereas classical invariance principles for ergodic Markov chains address the situation in which the time horizon of observations is much larger than the mixing time, the quality of approximation is questionable when this is not the case anymore -- even when starting the Markov chain in the invariant law. In this article, we prove quantitative and functional limit theorems for additive functionals along triangular arrays of stationary Gaussian Markov processes when the mixing time $t_{\text{mix}}$ scales sub-, super- and proportionately to the number of observations $n$. Our major finding is a phase-transition at $t_{\text{mix}}\asymp n$, together with the identification and interrelation properties of the emerging new limit processes at and before the mixing time.
format Preprint
id arxiv_https___arxiv_org_abs_2605_02713
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Before and beyond the mixing time: New approximations for additive functionals of stationary Gauss-Markov processes
Bellerino, Gabriele
Rohde, Angelika
Probability
60F05
Whereas classical invariance principles for ergodic Markov chains address the situation in which the time horizon of observations is much larger than the mixing time, the quality of approximation is questionable when this is not the case anymore -- even when starting the Markov chain in the invariant law. In this article, we prove quantitative and functional limit theorems for additive functionals along triangular arrays of stationary Gaussian Markov processes when the mixing time $t_{\text{mix}}$ scales sub-, super- and proportionately to the number of observations $n$. Our major finding is a phase-transition at $t_{\text{mix}}\asymp n$, together with the identification and interrelation properties of the emerging new limit processes at and before the mixing time.
title Before and beyond the mixing time: New approximations for additive functionals of stationary Gauss-Markov processes
topic Probability
60F05
url https://arxiv.org/abs/2605.02713