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This note studies monotone Markov chains, a subclass of Markov chains with extensive applications in operations research and economics. While the properties that ensure the global stability of these chains are well studied, their…

Probability · Mathematics 2024-09-20 Bar Light

This article aims to investigate sufficient conditions for the stability of stochastic differential equations with a random structure, particularly in contexts involving the presence of concentration points. The proof of asymptotic…

Probability · Mathematics 2023-05-22 Taras Lukashiv , Igor V. Malyk , Maryna Chepeleva , Petr V. Nazarov

We address stability of a class of Markovian discrete-time stochastic hybrid systems. This class of systems is characterized by the state-space of the system being partitioned into a safe or target set and its exterior, and the dynamics of…

Optimization and Control · Mathematics 2011-03-09 Debasish Chatterjee , Soumik Pal

This paper studies the exponential stability of random matrix products driven by a general (possibly unbounded) state space Markov chain. It is a cornerstone in the analysis of stochastic algorithms in machine learning (e.g. for parameter…

Machine Learning · Statistics 2021-02-02 Alain Durmus , Eric Moulines , Alexey Naumov , Sergey Samsonov , Hoi-To Wai

We develop a practical approach to establish the stability, that is, the recurrence in a given set, of a large class of controlled Markov chains. These processes arise in various areas of applied science and encompass important numerical…

Statistics Theory · Mathematics 2015-02-02 Christophe Andrieu , Vladislav B. Tadić , Matti Vihola

Order-preserving couplings are elegant tools for obtaining robust estimates of the time-dependent and stationary distributions of Markov processes that are too complex to be analyzed exactly. The starting point of this paper is to study…

Probability · Mathematics 2009-06-02 Lasse Leskelä

A general setting for nested subdivisions of a bounded real set into intervals defining the digits $X_1,X_2,...$ of a random variable $X$ with a probability density function $f$ is considered. Under the weak condition that $f$ is almost…

Probability · Mathematics 2026-01-14 Jesper Møller

The exact stochastic decomposition of non-Markovian dissipative quantum dynamics is combined with the time-dependent semiclassical initial value formalism. It is shown that even in the challenging regime of moderate friction and low…

Statistical Mechanics · Physics 2011-09-30 Werner Koch , Frank Großmann , Jürgen T. Stockburger , Joachim Ankerhold

Relation between equicontinuity, the so called e property and stability of Markov operators is studied. In particular, it is shown that any asymptotically stable Markov operator with an invariant measure such that the interior of its…

Probability · Mathematics 2017-10-09 Sander C. Hille , Tomasz Szarek , Maria A. Ziemlanska

We study limit theorems for partial sums of instantaneous functions of a homogeneous Markov chain on a general state space. The summands are heavy-tailed and the limits are stable distributions. The conditions imposed on the transition…

Probability · Mathematics 2018-08-14 Mohamed El Machkouri , Adam Jakubowski , Dalibor Volný

This paper integrates two strands of the literature on stability of general state Markov chains: conventional, total variation based results and more recent order-theoretic results. First we introduce a complete metric over Borel…

Probability · Mathematics 2024-10-02 Takashi Kamihigashi , John Stachurski

We provide a detailed discussion about the unitary and reduced evolution induced by family of Hamiltonian models describing a multilevel system, with a ground state and a possibly multilevel excited sector, coupled to a multimode boson…

Quantum Physics · Physics 2023-01-30 Dariusz Chruściński , Samaneh Hesabi , Davide Lonigro

Many economic models feature monotone Markov dynamics on state spaces that may be noncompact. Establishing existence, uniqueness, and stability of stationary distributions in such settings has required a patchwork of sufficient conditions,…

Probability · Mathematics 2026-04-07 Takashi Kamihigashi , John Stachurski

In this paper, we derive a simple drift condition for the stability of a class of two-dimensional Markov processes, for which one of the coordinates (also referred to as the {\em phase} for convenience) has a well understood behaviour…

Probability · Mathematics 2020-10-01 Stella Kapodistria , Seva Shneer

Model Predictive Control (MPC) is well understood in the deterministic setting, yet rigorous stability and performance guarantees for stochastic MPC remain limited to the consideration of terminal constraints and penalties. In contrast,…

Optimization and Control · Mathematics 2025-10-24 Jonas Schießl , Hannah Selder , Ruchuan Ou , Michael Heinrich Baumann , Timm Faulwasser , Lars Grüne

Markov combination is an operation that takes two statistical models and produces a third whose marginal distributions include those of the original models. Building upon and extending existing work in the Gaussian case, we develop Markov…

Statistics Theory · Mathematics 2025-09-24 Orlando Marigliano , Eva Riccomagno

A Markovian dichotomic system driven by a deterministic time-periodic force is analyzed in terms of the statistical properties of the switching events between the states. The consideration of the counting process of the switching events…

Statistical Mechanics · Physics 2009-11-10 Jesús Casado-Pascual , José Gómez-Ordóñez , M. Morillo

We prove exponential decay of pair correlations for 1D stationary point processes when spacings satisfy a Markov condition, geometric ergodicity, and a condition on exponential moments. The conditions are phrased for stationary sequences of…

Probability · Mathematics 2026-05-22 Yoon Jun Chan , Markus Heydenreich , Sabine Jansen

In many applications, the common assumption that a driving noise process affecting a system is independent or Markovian may not be realistic, but the noise process may be assumed to be stationary. To study such problems, this paper…

Probability · Mathematics 2018-01-08 Serdar Yüksel

Stochastic approximation is a framework unifying many random iterative algorithms occurring in a diverse range of applications. The stability of the process is often difficult to verify in practical applications and the process may even be…

Probability · Mathematics 2014-03-10 Christophe Andrieu , Matti Vihola
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