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We prove a functional limit theorem for vector-valued functionals of the fractional Ornstein-Uhlenbeck process, providing the foundation for the fluctuation theory of slow/fast systems driven by such a noise. Our main contribution is on the…

Probability · Mathematics 2023-03-07 Johann Gehringer , Xue-Mei Li

We show a new functional limit theorem for weakly dependent regularly varying sequences of random vectors. As it turns out, the convergence takes place in the space of R^d valued c\`{a}dl\`{a}g functions endowed with the so-called weak M1…

Probability · Mathematics 2013-08-19 Bojan Basrak , Danijel Krizmanić

We explore the limit of stochastic differential equations driven by some random processes satisfying singularly perturbed second order stochastic differential equations. The main tool we employ is the universal limit theorem in rough path…

Probability · Mathematics 2026-04-08 Qingming Zhao , Xueru Liu , Wei Wang

We use the martingale convergence method to get the weak convergence theorem on general functionals of partial sums of independent heavy-tailed random variables. The limiting process is the stochastic integral driven by $\alpha-$stable…

Statistics Theory · Mathematics 2014-11-18 Zhengyan Lin , Hanchao Wang

By using limit theorems of uniform mixing Markov processes and martingale difference sequences, the strong law of large numbers, central limit theorem, and the law of iterated logarithm are established for additive functionals of…

Probability · Mathematics 2019-04-08 Jianhai Bao , Feng-Yu Wang , Chenggui Yuan

We consider a system of differential equations in a fast long range dependent random environment and prove a homogenization theorem involving multiple scaling constants. The effective dynamics solves a rough differential equation, which is…

Probability · Mathematics 2019-12-02 Johann Gehringer , Xue-Mei Li

We consider autonomous stochastic ordinary differential equations (SDEs) and weak approximations of their solutions for a general class of sufficiently smooth path-dependent functionals f. Based on tools from functional It\^o calculus, such…

Probability · Mathematics 2016-06-15 Mihály Kovács , Felix Lindner

For a strictly stationary sequence of random variables we derive functional convergence of the joint partial sum and partial maxima process under joint regular variation with index $\alpha \in (0,2)$ and weak dependence conditions. The…

Probability · Mathematics 2019-10-08 Danijel Krizmanic

We establish functional limit theorems for ergodic sums of observables with power singularities for expanding circle maps. In the regime where the observables have infinite variance, we show that when rescaled by $N^{1/s}(\ln N)^\alpha$,…

Dynamical Systems · Mathematics 2025-09-03 Dmitry Dolgopyat , Sixu Liu

For a stationary sequence of random variables we derive a self-normalized functional limit theorem under joint regular variation with index $\alpha \in (0,2)$ and weak dependence conditions. The convergence takes place in the space of…

Probability · Mathematics 2026-05-12 Danijel Krizmanic

For a strictly stationary sequence of $\mathbb{R}_{+}^{d}$--valued random vectors we derive functional convergence of partial maxima stochastic processes under joint regular variation and weak dependence conditions. The limit process is an…

Probability · Mathematics 2016-07-14 Danijel Krizmanić

We consider a random process as a solution of stochastic differential equations with dependence of the coefficients on small parameter $\varepsilon$ and we suppose that the drift coefficients of these equations are unbounded on the…

Probability · Mathematics 2023-12-15 Ivan H. Krykun

We present an abstract framework to study weak convergence of numerical approximations of linear stochastic partial differential equations driven by additive L\'evy noise. We first derive a representation formula for the error which we then…

Probability · Mathematics 2016-02-25 Mihály Kovács , Felix Lindner , René L. Schilling

We obtain general weak existence and stability results for stochastic convolution equations with jumps under mild regularity assumptions, allowing for non-Lipschitz coefficients and singular kernels. Our approach relies on weak convergence…

Probability · Mathematics 2021-12-22 Eduardo Abi Jaber , Christa Cuchiero , Martin Larsson , Sergio Pulido

We aim to generalize the homogenisation theorem in \cite{Gehringer-Li-tagged} for a passive tracer interacting with a fractional Gau{\ss}ian noise to also cover fractional non-Gau{\ss}ian noises. To do so we analyse limit theorems for…

Probability · Mathematics 2020-09-17 Johann Gehringer

Consider a family of random ordinary differential equations on a manifold driven by vector fields of the form $\sum_kY_k\alpha_k(z_t^\epsilon(\omega))$ where $Y_k$ are vector fields, $\epsilon$ is a positive number, $z_t^\epsilon$ is a…

Probability · Mathematics 2017-05-22 Xue-Mei Li

In this paper we address the convergence of stochastic approximation when the functions to be minimized are not convex and nonsmooth. We show that the "mean-limit" approach to the convergence which leads, for smooth problems, to the ODE…

Optimization and Control · Mathematics 2018-05-08 Szymon Majewski , Błażej Miasojedow , Eric Moulines

We prove an extension theorem for local solutions of the 3d incompressible Euler equations. More precisely, we show that if a smooth vector field satisfies the Euler equations in a spacetime region $\Omega\times(0,T)$, one can choose an…

Analysis of PDEs · Mathematics 2025-10-01 Alberto Enciso , Javier Peñafiel-Tomás , Daniel Peralta-Salas

The paper concerns the $d$-dimensional stochastic approximation recursion, $$ \theta_{n+1}= \theta_n + \alpha_{n + 1} f(\theta_n, \Phi_{n+1}) $$ where $ \{ \Phi_n \}$ is a stochastic process on a general state space, satisfying a…

Statistics Theory · Mathematics 2024-11-18 Vivek Borkar , Shuhang Chen , Adithya Devraj , Ioannis Kontoyiannis , Sean Meyn

In this paper, we prove convergence in distribution of Langevin processes in the overdamped asymptotics. The proof relies on the classical perturbed test function (or corrector) method, which is used both to show tightness in path space,…

Probability · Mathematics 2019-03-11 Mathias Rousset , Yushun Xu , Pierre-André Zitt
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