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We construct a family of genealogy-valued Markov processes that are induced by a continuous-time Markov population process. We derive exact expressions for the likelihood of a given genealogy conditional on the history of the underlying…

Probability · Mathematics 2022-01-26 Aaron A. King , Qianying Lin , Edward L. Ionides

Given a possibly discontinuous, bounded function $f:\mathbb{R}\mapsto\mathbb{R}$, we consider the set of generalized flows, obtained by assigning a probability measure on the set of Carath\'eodory solutions to the ODE ~$\dot x = f(x)$. The…

Classical Analysis and ODEs · Mathematics 2020-09-15 Alberto Bressan , Marco Mazzola , Khai T. Nguyen

Comparison results for Markov processes w.r.t. function class induced (integral) stochastic orders have a long history. The most general results so far for this problem have been obtained based on the theory of evolution systems on Banach…

Probability · Mathematics 2019-11-12 Benedikt Köpfer , Ludger Rüschendorf

Stricker's theorem states that a Gaussian process is a semimartingale in its natural filtration if and only if it is the sum of an independent increment Gaussian process and a Gaussian process of finite variation, see [1983, Z. Wahrsch.…

Probability · Mathematics 2014-12-15 Andreas Basse-O'Connor , Jan Rosiński

We consider the stochastic differential equations of the form \begin{equation*} \begin{cases} dX^ x(t) = \sigma(X(t-)) dL(t) \\ X^ x(0)=x,\quad x\in\mathbb{R}^ d, \end{cases} \end{equation*} where $\sigma:\mathbb{R}^ d\to \mathbb{R}^ d$ is…

Probability · Mathematics 2015-08-20 Pani W. Fernando , Erika Hausenblas , Paul Razafimandimby

We define analogues of Brownian motion on the triadic Cantor set by introducing a few natural requirements on the Markov semigroup. We give a detailed description of these symmetric self-similar processes and study their properties such as…

Probability · Mathematics 2008-10-22 Yuri Bakhtin

We propose a general approach for quantitative convergence analysis of non-reversible Markov processes, based on the concept of second-order lifts and a variational approach to hypocoercivity. To this end, we introduce the flow Poincar{\'e}…

Analysis of PDEs · Mathematics 2025-07-22 Andreas Eberle , Arnaud Guillin , Leo Hahn , Francis Lörler , Manon Michel

In this paper we prove the stochastic homeomorphism flow property and the strong Feller property for stochastic differential equations with sigular time dependent drifts and Sobolev diffusion coefficients. Moreover, the local well posedness…

Probability · Mathematics 2011-05-04 Xicheng Zhang

The notion of a successful coupling of Markov processes, based on the idea that both components of the coupled system ``intersect'' in finite time with probability one, is extended to cover situations when the coupling is unnecessarily…

Probability · Mathematics 2007-05-23 Michael Blank , Sergey Pirogov

Semilinear stochastic evolution equations with multiplicative L\'evy noise and monotone nonlinear drift are considered. Unlike other similar work we do not impose coercivity conditions on coefficients. Existence and uniqueness of the mild…

Probability · Mathematics 2013-12-03 Erfan Salavati , Bijan Z. Zangeneh

Recently, a class of stochastic processes known as piecewise deterministic Markov processes has been used to define continuous-time Markov chain Monte Carlo algorithms with a number of attractive properties, including compatibility with…

Computation · Statistics 2019-06-03 Alexander Terenin , Daniel Thorngren

In this paper, we outline a model of graph (or network) dynamics based on two ingredients. The first ingredient is a Markov chain on the space of possible graphs. The second ingredient is a semi-Markov counting process of renewal type. The…

Probability · Mathematics 2015-05-28 Marco Raberto , Fabio Rapallo , Enrico Scalas

In this article, we solve the problem of the long time behaviour of transition probabilities of time-inhomogeneous Markov processes and give a unified approach to stochastic differential equations (SDEs) with periodic, quasi-periodic,…

Probability · Mathematics 2023-07-18 Chunrong Feng , Baoyou Qu , Huaizhong Zhao

A novel class of non-reversible Markov chain Monte Carlo schemes relying on continuous-time piecewise-deterministic Markov Processes has recently emerged. In these algorithms, the state of the Markov process evolves according to a…

Methodology · Statistics 2018-05-16 Paul Vanetti , Alexandre Bouchard-Côté , George Deligiannidis , Arnaud Doucet

In this note, we propose two different approaches to rigorously justify a pseudo-Markov property for controlled diffusion processes which is often (explicitly or implicitly) used to prove the dynamic programming principle in the stochastic…

Probability · Mathematics 2015-01-19 Julien Claisse , Denis Talay , Xiaolu Tan

We study the long time behaviour of a Markov process evolving in $\mathbb{N}$ and conditioned not to hit 0. Assuming that the process comes back quickly from infinity, we prove that the process admits a unique quasi-stationary distribution…

Probability · Mathematics 2013-04-04 Servet Martinez , Jaime San Martin , Denis Villemonais

The theory of flows was used as a crucial tool in the recent proof by Margolis, Rhodes and Schilling that Krohn-Rhodes complexity is decidable. In this paper we begin a systematic study of aperiodic flows. We give the foundations of the…

Dynamical Systems · Mathematics 2025-02-04 Stuart Margolis , John Rhodes

In this paper, we establish a version of the central limit theorem for Markov-Feller continuous time processes (with a Polish state space) that are exponentially ergodic in the bounded-Lipschitz distance and enjoy a continuous form of the…

Probability · Mathematics 2023-10-09 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

We consider a Markovian evolution on point processes, the $\Psi$--process, on the unit interval in which points are added according to a rule that depends only on the spacings of the existing point configuration. Having chosen a spacing, a…

Probability · Mathematics 2020-07-01 Pascal Maillard , Elliot Paquette

We provide a framework for speeding up algorithms for time-bounded reachability analysis of continuous-time Markov decision processes. The principle is to find a small, but almost equivalent subsystem of the original system and only analyse…

Systems and Control · Computer Science 2018-07-26 Pranav Ashok , Yuliya Butkova , Holger Hermanns , Jan Křetínský
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