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In this paper, we study an approximation scheme for L\'evy processes with drift in terms of a representation that is akin to the celebrated Mehler formula for L\'evy-Ornstein-Uhlenbeck processes. The approximation scheme is based on a…

Probability · Mathematics 2025-11-25 Max Nendel

We establish exact rates of convergence in the $p$-Wasserstein distance for the empirical measure of a class of non-symmetric jump processes, which are subordinated to a diffusion process on a compact Riemannian manifold. For the quadratic…

Probability · Mathematics 2025-10-01 René L. Schilling , Bingyao Wu

We establish the exponential convergence with respect to the $L^1$-Wasserstein distance and the total variation for the semigroup corresponding to the stochastic differential equation (SDE) $$d X_t=d Z_t+b(X_t)\,d t,$$ where $(Z_t)_{t\ge0}$…

Probability · Mathematics 2018-05-14 Dejun Luo , Jian Wang

Generally the convergence rate in exponential ergodicity $\lambda$ is an upper bound for the convergence rate $\kappa$ in uniform ergodicity for a Markov process, that is $\lambda\geqslant\kappa$. In this paper, we prove that…

Probability · Mathematics 2022-01-19 Yong-Hua Mao , Tao Wang

We investigate some asymptotic properties of general Markov processes conditioned not to be absorbed by moving boundaries. We first give general criteria involving an exponential convergence towards the Q-process, that is the law of the…

Probability · Mathematics 2020-05-13 William Oçafrain

Tau leap schemes were originally designed for the efficient time stepping of discrete state and continuous in time Markov processes arising in stochastic chemical kinetics. Previous convergence results on tau leaping schemes have been…

Numerical Analysis · Mathematics 2015-12-09 Muruhan Rathinam

In this paper, conditions for transience, recurrence, ergodicity and strong, subexponential (polynomial) and exponential ergodicity of a class of Feller processes are derived. The conditions are given in terms of the coefficients of the…

Probability · Mathematics 2016-04-04 Nikola Sandrić

We construct a Hunt process that can be described as an isotropic $\alpha$-stable L\'evy process reflected from the complement of a bounded open Lipschitz set. In fact, we introduce a new analytic method for concatenating Markov processes.…

Probability · Mathematics 2024-10-07 Krzysztof Bogdan , Markus Kunze

Perturbation theory for Markov chains addresses the question how small differences in the transitions of Markov chains are reflected in differences between their distributions. We prove powerful and flexible bounds on the distance of the…

Computation · Statistics 2017-02-27 Daniel Rudolf , Nikolaus Schweizer

In this paper, we establish sharp upper and lower bounds on the convergence rate of the empirical measures of point processes under the Wasserstein distance. To this end, we first introduce a new metric on the space of counting measures…

Statistics Theory · Mathematics 2026-04-28 Dongzhou Huang , Tianyi Jiang , Haonan Wang

Explicit calculations in dimension one show for Schur stable autoregressive processes with standard Gaussian noise that the ergodic convergence in the Wasserstein-$2$ distance is essentially given by the sum of the mean, which decays…

Probability · Mathematics 2026-01-09 Gerardo Barrera , Paulo Henrique da Costa , Michael A. Högele

We consider periodic Markov chains with absorption. Applying to iterates of this periodic Markov chain criteria for the exponential convergence of conditional distributions of aperiodic absorbed Markov chains, we obtain exponential…

Probability · Mathematics 2022-11-08 Nicolas Champagnat , Denis Villemonais

We develop a powerful and general method to provide rigorous and accurate upper and lower bounds for Lyapunov exponents of stochastic flows. Our approach is based on computer-assisted tools, the adjoint method and established results on the…

Dynamical Systems · Mathematics 2025-06-02 Maxime Breden , Hugo Chu , Jeroen S. W. Lamb , Martin Rasmussen

Configurable Markov Decision Processes (Conf-MDPs) have recently been introduced as an extension of the traditional Markov Decision Processes (MDPs) to model the real-world scenarios in which there is the possibility to intervene in the…

Machine Learning · Computer Science 2024-02-22 Alberto Maria Metelli

We provide explicit expressions for the constants involved in the characterisation of ergodicity of sub-geometric Markov chains. The constants are determined in terms of those appearing in the assumed drift and one-step minorisation…

Probability · Mathematics 2014-03-18 Christophe Andrieu , Gersende Fort , Matti Vihola

By refining a recent result of Xie and Zhang, we prove the exponential ergodicity under a weighted variation norm for singular SDEs with drift containing a local integrable term and a coercive term. This result is then extended to singular…

Probability · Mathematics 2023-03-10 Feng-Yu Wang

For near-critical, transient Markov chains on the non-negative integers in the Lamperti regime, where the mean drift at $x$ decays as $1/x$ as $x \to \infty$, we quantify degree of transience via existence of moments for conditional return…

Probability · Mathematics 2024-05-07 Chak Hei Lo , Mikhail V. Menshikov , Andrew R. Wade

We introduce a unified framework to estimate the convergence of Markov chains to equilibrium in Wasserstein distance. The framework can provide convergence bounds with rates ranging from polynomial to exponential, all derived from a…

Probability · Mathematics 2025-06-09 Yanlin Qu , Jose Blanchet , Peter Glynn

Coupling by reflection mixed with synchronous coupling is constructed for a class of stochastic differential equations (SDEs) driven by L\'{e}vy noises. As an application, we establish the exponential contractivity of the associated…

Statistics Theory · Mathematics 2016-03-18 Jian Wang

Let $k\in (d,\infty]$ and consider the $k*$-distance $$\|\mu-\nu\|_{k*}:= \sup\Big\{|\mu(f)-\nu(f)|:\ f\in\B_b(\R^d),\ \|f\|_{\tt L^k}:=\sup_{x\in \R^d}\|1_{B(x,1)}f\|_{L^k}\le 1\Big\}$$ between probability measures on $\R^d$. The…

Probability · Mathematics 2025-08-20 Xing Huang , Feng-Yu Wang
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