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We present a data-driven model predictive control scheme for chance-constrained Markovian switching systems with unknown switching probabilities. Using samples of the underlying Markov chain, ambiguity sets of transition probabilities are…

Optimization and Control · Mathematics 2020-10-02 Mathijs Schuurmans , Panagiotis Patrinos

We consider a discrete time semi-Markov process where the characteristics defining the process depend on a small perturbation parameter. It is assumed that the state space consists of one finite communicating class of states and, in…

Probability · Mathematics 2016-03-21 Mikael Petersson

We develop a quenched thermodynamic formalism for open random dynamical systems generated by finitely branched, piecewise-monotone mappings of the interval. The openness refers to the presence of holes in the interval, which terminate…

Dynamical Systems · Mathematics 2024-11-06 Jason Atnip , Gary Froyland , Cecilia Gonzalez-Tokman , Sandro Vaienti

We study properties of the Laplace transforms of non-negative additive functionals of Markov chains. We are namely interested in a multiplicative ergodicity property used in [18] to study bifurcating processes with ancestral dependence. We…

Probability · Mathematics 2015-09-11 Loïc Hervé , Françoise Pène

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

In this work, we study a natural nonparametric estimator of the transition probability matrices of a finite controlled Markov chain. We consider an offline setting with a fixed dataset, collected using a so-called logging policy. We develop…

Machine Learning · Statistics 2026-03-17 Imon Banerjee , Harsha Honnappa , Vinayak Rao

We consider invariant transports of stationary random measures on $\mathbb{R}^d$ and establish natural mixing criteria that guarantee persistence of asymptotic variances. To check our mixing assumptions, which are based on two-point Palm…

Probability · Mathematics 2025-06-09 Michael A. Klatt , Günter Last , Luca Lotz , D. Yogeshwaran

We develop operator renewal theory for flows and apply this to infinite ergodic theory. In particular we obtain results on mixing for a large class of infinite measure semiflows. Examples of systems covered by our results include…

Dynamical Systems · Mathematics 2014-04-11 Ian Melbourne , Dalia Terhesiu

We establish the conditioned stochastic stability of equilibrium states for H\"older potentials on uniformly hyperbolic sets. While standard stochastic stability characterises measures on attractors, we analyse the statistics of transient…

Dynamical Systems · Mathematics 2025-12-22 Bernat Bassols Cornudella , Matheus M. Castro

We study the asymptotic behavior of Markov operators $P_\mu$ defined by convolution with a probability measure $\mu$ on the unit circle $\mathbb T$. We prove that when $\mu$ is adapted, $P_\mu$ satisfies Doeblin's condition if and only if…

Probability · Mathematics 2026-01-27 Guy Cohen , Michael Lin

A Markov-switching observation-driven model is a stochastic process $((S_t,Y_t))_{t \in \mathbb{Z}}$ where $(S_t)_{t \in \mathbb{Z}}$ is an unobserved Markov chain on a finite set and $(Y_t)_{t \in \mathbb{Z}}$ is an observed stochastic…

Econometrics · Economics 2025-12-30 Frederik Krabbe

We are concerned with the absolute continuity of stationary distributions corresponding to some piecewise deterministic Markov process, being typically encountered in biological models. The process under investigation involves a…

Probability · Mathematics 2024-03-26 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

We derive sufficient conditions for a probability measure on a finite product space (a spin system) to satisfy a (modified) logarithmic Sobolev inequality. We establish these conditions for various examples, such as the (vertex-weighted)…

Probability · Mathematics 2020-05-15 Holger Sambale , Arthur Sinulis

The method to design exponentially stable adaptive observers is proposed for linear time-invariant systems parameterized by unknown physical parameters. Unlike existing adaptive solutions, the system state-space matrices A, B are not…

Systems and Control · Electrical Eng. & Systems 2023-08-22 Anton Glushchenko , Konstantin Lastochkin

Quantum chaotic systems exhibit certain universal statistical properties that closely resemble predictions from random matrix theory (RMT). With respect to observables, it has recently been conjectured that, when truncated to a sufficiently…

Statistical Mechanics · Physics 2026-01-16 Mariel Kempa , Markus Kraft , Robin Steinigeweg , Jochen Gemmer , Jiaozi Wang

This paper considers a class of reinforcement-based learning (namely, perturbed learning automata) and provides a stochastic-stability analysis in repeatedly-played, positive-utility, finite strategic-form games. Prior work in this class of…

Computer Science and Game Theory · Computer Science 2019-01-29 Georgios C. Chasparis

In this paper, we consider concentration phenomenon of semiclassical states to the following $2M$-component reaction-diffusion system in $\R \times \R^N$, \begin{align*} \left\{ \begin{aligned} \partial_t u &=\eps^2 \Delta_x u-u-V(x)v +…

Analysis of PDEs · Mathematics 2022-12-29 Tianxiang Gou , Zhitao Zhang

First-passage properties are central to the kinetics of target-search processes. Theoretical approaches so far primarily focused on predicting first-passage statistics for a given process or model. In practice, however, one faces the…

Statistical Mechanics · Physics 2025-01-08 Rick Bebon , Aljaz Godec

Qualitative opacity of a secret is a security property, which means that a system trajectory satisfying the secret is observation-equivalent to a trajectory violating the secret. In this paper, we study how to synthesize a control policy…

Formal Languages and Automata Theory · Computer Science 2024-12-04 Sumukha Udupa , Jie Fu

We study the properties of a subclass of stochastic processes called discrete time nonlinear Markov chains with an aggregator, which naturally appear in various topics such as strategic queueing systems, inventory dynamics, opinion…

Probability · Mathematics 2025-12-24 Bar Light
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