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We provide a criterion for establishing lower bounds on the rate of convergence in $f$-variation of a continuous-time ergodic Markov process to its invariant measure. The criterion consists of novel super- and submartingale conditions for…

Probability · Mathematics 2024-04-16 Miha Brešar , Aleksandar Mijatović

Strong invariance principles describe the error term of a Brownian approximation of the partial sums of a stochastic process. While these strong approximation results have many applications, the results for continuous-time settings have…

Statistics Theory · Mathematics 2022-06-17 Ardjen Pengel , Joris Bierkens

We propose an extension of ergodic theory which focuses on the identification of ergodicity in terms of the uniqueness of the invariant measure. We first explain the concept for the doubling maps, which can be analyzed using Fourier…

Dynamical Systems · Mathematics 2015-12-11 Haakan Hedenmalm , Alfonso Montes-Rodriguez

We consider the problem of inference for nonlinear, multivariate diffusion processes, satisfying It\^o stochastic differential equations (SDEs), using data at discrete times that may be incomplete and subject to measurement error. Our…

Computation · Statistics 2021-09-27 Andrew Golightly , Chris Sherlock

We study space-time fluctuations around a characteristic line for a one-dimensional interacting system known as the random average process. The state of this system is a real-valued function on the integers. New values of the function are…

Probability · Mathematics 2007-09-12 Marton Balazs , Firas Rassoul-Agha , Timo Seppalainen

We consider integer-valued random walks with independent but not identically distributed increments, and extend to this context several classical estimates, including a local limit theorem, precise small-ball estimates (both conditional on…

Probability · Mathematics 2025-11-13 Sébastien Ott , Yvan Velenik

The aim of this paper is to show how extracting dynamical behavior and ergodic properties from deterministic chaos with the assistance of exact invariant measures. On the one hand, we provide an approach to deal with the inverse problem of…

Chaotic Dynamics · Physics 2015-06-24 Roberto Venegeroles

The large-deviation method allows to characterize an ergodic counting process in terms of a thermodynamic frame where a free energy function determines the asymptotic non-stationary statistical properties of its fluctuations. Here, we study…

Statistical Mechanics · Physics 2011-12-13 Adrian A. Budini

We study the stochastic behavior of heterogeneous diffusion processes with the power-law dependence $D(x)\sim|x|^{\alpha}$ of the generalized diffusion coefficient encompassing sub- and superdiffusive anomalous diffusion. Based on…

Statistical Mechanics · Physics 2014-12-24 Andrey G. Cherstvy , Ralf Metzler

We discuss the relationship between discrete-time processes (chains) and one-dimensional Gibbs measures. We consider finite-alphabet (finite-spin) systems, possibly with a grammar (exclusion rule). We establish conditions for a stochastic…

Probability · Mathematics 2007-05-23 Roberto Fernandez , Gregory Maillard

We consider the limiting behavior of fluctuations of small noise diffusions with multiple scales around their homogenized deterministic limit. We allow full dependence of the coefficients on the slow and fast motion. These processes arise…

Probability · Mathematics 2015-02-20 Konstantinos Spiliopoulos

We investigate simple models for strictly non-ergodic stochastic processes $x_t$ ($t$ being the discrete time step) focusing on the expectation value $v$ and the standard deviation $\delta v$ of the empirical variance $v[x]$ of finite time…

Disordered Systems and Neural Networks · Physics 2021-11-23 G. George , L. Klochko , A. N. Semenov , J. Baschnagel , J. P. Wittmer

We investigate the limiting behavior of discrete determinantal point processes (DPPs) towards continuous DPPs when the size of the set to sample from goes to infinity. We propose a non-asymptotic characterization of this limit in terms of…

Probability · Mathematics 2026-03-03 Hugo Jaquard , Nicolas Keriven

We classify the locally finite ergodic invariant measures of certain infinite interval exchange transformations (IETs). These transformations naturally arise from return maps of the straight-line flow on certain translation surfaces, and…

Dynamical Systems · Mathematics 2016-01-20 W. Patrick Hooper

This paper provides rates of convergence for empirical (generalised) barycenters on compact geodesic metric spaces under general conditions using empirical processes techniques. Our main assumption is termed a variance inequality and…

Statistics Theory · Mathematics 2019-06-03 Adil Ahidar-Coutrix , Thibaut Le Gouic , Quentin Paris

We obtain explicit criteria for both exponential ergodicity and strong ergodicity for one-dimensional time-changed symmetric stable processes with $\alpha\in(1,2)$. Explicit lower bounds for ergodic convergence rates are given.

Probability · Mathematics 2021-12-06 Tao Wang

We consider a simple mean reverting diffusion process, with piecewise constant drift and diffusion coefficients, discontinuous at a fixed threshold. We discuss estimation of drift and diffusion parameters from discrete observations of the…

Statistics Theory · Mathematics 2024-03-12 Sara Mazzonetto , Paolo Pigato

A subshift with linear block complexity has at most countably many ergodic measures, and we continue of the study of the relation between such complexity and the invariant measures. By constructing minimal subshifts whose block complexity…

Dynamical Systems · Mathematics 2019-02-26 Van Cyr , Bryna Kra

We consider infinite Galton-Watson trees without leaves together with i.i.d.~random variables called marks on each of their vertices. We define a class of flow rules on marked Galton-Watson trees for which we are able, under some algebraic…

Probability · Mathematics 2018-05-07 Pierre Rousselin

We provide quantitative bounds for the long time behavior of a class of Piecewise Deterministic Markov Processes with state space Rd \times E where E is a finite set. The continuous component evolves according to a smooth vector field that…

Probability · Mathematics 2012-12-07 Michel Benaïm , Stéphane Le Borgne , Florent Malrieu , Pierre-André Zitt
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