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We construct a stochastic fluid process with an underlying piecewise deterministic Markov process (PDMP) akin to the one used in the construction of the rational arrival process (RAP), which we call the RAP-modulated fluid process. As…

Probability · Mathematics 2021-01-12 Nigel G. Bean , Giang T. Nguyen , Bo F. Nielsen , Oscar Peralta

The family of multivariate skew-normal distributions has many interesting properties. It is shown here that these hold for a general class of skew-elliptical distributions. For this class, several stochastic representations are established…

Statistics Theory · Mathematics 2023-09-18 Chuancun Yin , Narayanaswamy Balakrishnan

This paper contributes to the study of class $(\Sigma^{r})$ as well as the c\`adl\`ag semi-martingales of class $(\Sigma)$, whose finite variational part is c\`adl\`ag instead of continuous. The two above-mentioned classes of stochastic…

Probability · Mathematics 2021-08-30 Fulgence Eyi Obiang , Paule Joyce Mbenangoye , Octave Moutsinga

Misra, Prigogine and Courbage (MPC) demonstrated the possibility of obtaining stochastic Markov processes from deterministic dynamics simply through a "change of representation" which involves no loss of information provided the dynamical…

Mathematical Physics · Physics 2007-05-23 F. Gomez

If the prime numbers are pseudo-randomly distributed, then analogy with quantum systems suggests that counting primes might be modeled by a non-homogeneous Poisson process. Consequently, postulating underlying gamma statistics, more-or-less…

Number Theory · Mathematics 2014-11-19 J. LaChapelle

A general affine Markov semigroup is formulated as the convolution of a homogeneous one with a skew convolution semigroup. We provide some sufficient conditions for the regularities of the homogeneous affine semigroup and the skew…

Probability · Mathematics 2007-06-13 D. A. Dawson , Zenghu Li

We prove a stochastic averaging theorem for stochastic differential equations in which the slow and the fast variables interact. The approximate Markov fast motion is a family of Markov process with generator ${\mathcal L}_x$ for which we…

Probability · Mathematics 2019-02-19 Xue-Mei Li

We study a random process with reinforcement, which evolves following the dynamics of a given diffusion process in a bounded domain and is resampled according to its occupation measure when it reaches the boundary. We show that its…

Probability · Mathematics 2021-02-16 Michel Benaïm , Nicolas Champagnat , Denis Villemonais

We study controlled differential equations driven by a rough path (in the sense of T. Lyons) with an additional, possibly unbounded drift term. We show that the equation induces a solution flow if the drift grows at most linearly.…

Probability · Mathematics 2016-05-19 Sebastian Riedel , Michael Scheutzow

For a class of piecewise deterministic Markov processes, the supports of the invariant measures are characterized. This is based on the analysis of controllability properties of an associated deterministic control system. Its invariant…

Dynamical Systems · Mathematics 2018-04-05 Michel Benaïm , Fritz Colonius , Lettau Ralph

We introduce a class of stochastic advection problems amenable to analysis of turbulent transport. The statistics of the flow field are represented as a continuous time Markov process, a choice that captures the intuitive notion of…

Fluid Dynamics · Physics 2022-12-01 Andre N. Souza , Tyler Lutz , Glenn R. Flierl

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

We consider a semi-discrete finite element approximation for a system consisting of the evolution of a planar curve evolving by forced curve shortening flow inside a given bounded domain $\Omega \subset \mathbb{R}^2$, such that the curve…

Numerical Analysis · Mathematics 2020-03-17 Vanessa Styles , James Van Yperen

Ito's construction of Markovian solutions to stochastic equations driven by a L\'evy noise is extended to nonlinear distribution dependent integrands aiming at the effective construction of linear and nonlinear Markov semigroups and the…

Probability · Mathematics 2022-05-03 Vassili N. Kolokoltsov

Generative flows and diffusion models have been predominantly trained on ordinal data, for example natural images. This paper introduces two extensions of flows and diffusion for categorical data such as language or image segmentation:…

Machine Learning · Statistics 2021-10-25 Emiel Hoogeboom , Didrik Nielsen , Priyank Jaini , Patrick Forré , Max Welling

We study average flow properties in porous media using a two-dimensional network simulator. It models the dynamics of two-phase immiscible bulk flow where film flow can be neglected. The boundary conditions are biperiodic which provide a…

Soft Condensed Matter · Physics 2007-05-23 Henning Arendt Knudsen , Alex Hansen

We consider the task of filtering a dynamic parameter evolving as a diffusion process, given data collected at discrete times from a likelihood which is conjugate to the marginal law of the diffusion, when a generic dual process on a…

Probability · Mathematics 2023-11-29 Guillaume Kon Kam King , Andrea Pandolfi , Marco Piretto , Matteo Ruggiero

We consider diffusion processes with a spatially varying diffusivity giving rise to anomalous diffusion. Such heterogeneous diffusion processes are analysed for the cases of exponential, power-law, and logarithmic dependencies of the…

Statistical Mechanics · Physics 2017-09-13 Andrey G. Cherstvy , Ralf Metzler

Let $(\mathcal{E},D(\mathcal{E}))$ be a quasi-regular semi-Dirichlet form and $(X_t)_{t\geq0}$ be the associated Markov process. For $u\in D(\mathcal{E})_{loc}$, denote $A_t^{[u]}:=\tilde{u}(X_{t})-\tilde{u}(X_{0})$ and…

Probability · Mathematics 2014-06-11 Chuan-Zhong Chen , Li Ma , Wei Sun

This paper presents a study of power series distributions (PSD) with prescribed covariance characteristics. Such distributions constitute a fundamental class in probability theory and mathematical statistics, as they generalize a wide range…

Statistics Theory · Mathematics 2025-12-23 Oleksandr Volkov , Yurii Volkov , Nataliia Voinalovych