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It is well known that ergodic invariant measures for order preserving two-sided time random dynamical systems(RDS) on the real line $\mathbb R$ are Dirac. In the present note this is shown to hold also for one-sided time RDS.

Dynamical Systems · Mathematics 2026-02-18 Hans Crauel

We develop sampling methods, which consist of Gaussian invariant versions of random walk Metropolis (RWM), Metropolis adjusted Langevin algorithm (MALA) and second order Hessian or Manifold MALA. Unlike standard RWM and MALA we show that…

Machine Learning · Statistics 2025-06-27 Michalis K. Titsias , Angelos Alexopoulos , Siran Liu , Petros Dellaportas

The invariant measure is a fundamental object in the theory of Markov processes. In finite dimensions a Markov process is defined by transition rates of the corresponding stochastic matrix. The Markov tree theorem provides an explicit…

Probability · Mathematics 2019-10-08 Artur Stephan

In this paper we study splittings of a Poisson point process which are equivariant under a conservative transformation. We show that, if the Cartesian powers of this transformation are all ergodic, the only ergodic splitting is the obvious…

Probability · Mathematics 2018-11-21 Elise Janvresse , Emmanuel Roy , Thierry De La Rue

We consider a stochastic electroconvection model describing the nonlinear evolution of a surface charge density in a two-dimensional fluid with additive stochastic forcing. We prove the existence and uniqueness of solutions, we define the…

Analysis of PDEs · Mathematics 2022-10-20 Elie Abdo , Nathan Glatt-Holtz , Mihaela Ignatova

This paper deals with ergodic theorems for particular time-inhomogeneous Markov processes, whose the time-inhomogeneity is asymptotically periodic. Under a Lyapunov/minorization condition, it is shown that, for any measurable bounded…

Probability · Mathematics 2022-04-06 William Oçafrain

We study a limit behavior of a sequence of Markov processes (or Markov chains) such that their distributions outside of any neighborhood of a "singular" point attract to some probability law. In any neighborhood of this point the behavior…

Probability · Mathematics 2015-09-14 Andrey Pilipenko , Yuriy Prykhodko

Nonlinear Markov chains with finite state space have been introduced in Kolokoltsov (2010). The characteristic property of these processes is that the transition probabilities do not only depend on the state, but also on the distribution of…

Probability · Mathematics 2020-07-07 Berenice Anne Neumann

Dynamic heterogeneity has often been modeled by assuming that a single-particle observable, fluctuating at a molecular scale, is influenced by its coupling to environmental variables fluctuating on a second, perhaps slower, time scale.…

Condensed Matter · Physics 2009-11-07 Gregor Diezemann , Gerald Hinze , Hans Sillescu

We are studying stationary random processes with conditional polynomial moments that allow a continuous path modification. Processes with continuous path modification, are important because they are relatively easy to simulate. One does not…

Probability · Mathematics 2024-11-21 Paweł J. Szabłowski

In this article we study (possibly degenerate) stochastic differential equations (SDE) with irregular (or discontiuous) coefficients, and prove that under certain conditions on the coefficients, there exists a unique almost everywhere…

Probability · Mathematics 2009-08-18 Xicheng Zhang

This paper deals with the existence and limiting behavior of invariant measures of the stochastic Landau-Lifshitz-Bloch equation driven by linear multiplicative noise and additive noise defined in the entire space $\mathbb{R}^d$ for…

Analysis of PDEs · Mathematics 2024-10-10 Daiwen Huang , Zhaoyang Qiu , Bixiang Wang

We prove that diffusion equations with a space-time stationary and ergodic, divergence-free drift homogenize in law to a deterministic stochastic partial differential equation with Stratonovich transport noise. In the absence of spatial…

Probability · Mathematics 2022-08-01 Benjamin Fehrman

As a starting point we prove a functional central limit theorem for estimators of the invariant measure of a geometrically ergodic Harris-recurrent Markov chain in a multi-scale space. This allows to construct confidence bands for the…

Statistics Theory · Mathematics 2020-06-12 Jakob Söhl , Mathias Trabs

The long time behaviour of solutions to generalised stochastic porous media equations on bounded domains with Dirichlet boundary data is studied. We focus on a degenerate form of nonlinearity arising in self-organised criticality. Based on…

Probability · Mathematics 2019-09-12 Marius Neuß

A stochastic hybrid system, also known as a switching diffusion, is a continuous-time Markov process with state space consisting of discrete and continuous parts. We consider parametric estimation of theQmatrix for the discrete state…

Probability · Mathematics 2020-10-14 Masaaki Fukasawa

Hamiltonian systems are a classical example in the ergodic theory of flows with an invariant measure. In this matter, we present a brief introduction to measure theory and prove the Poincare recurrence theorem to present the conditions for…

Dynamical Systems · Mathematics 2025-09-12 Daniel Ferreira Lopes

We consider a hidden Markov model, where the signal process, given by a diffusion, is only indirectly observed through some noisy measurements. The article develops a variational method for approximating the hidden states of the signal…

Optimization and Control · Mathematics 2016-10-26 Tobias Sutter , Arnab Ganguly , Heinz Koeppl

We study regularity properties for invariant measures of semilinear diffusions in a separable Hilbert space. Based on a pathwise estimate for the underlying stochastic convolution, we prove a priori estimates on such invariant measures. As…

Probability · Mathematics 2022-11-15 Abdelhadi Es-Sarhir , Wilhelm Stannat

This paper provides a general and abstract approach to approximate ergodic regimes of Markov and Feller processes. More precisely, we show that the recursive algorithm presented in Lamberton & Pages (2002) and based on simulation algorithms…

Probability · Mathematics 2018-01-17 Gilles Pagès , Clément Rey