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Given a domain G, a reflection vector field d(.) on the boundary of G, and drift and dispersion coefficients b(.) and \sigma(.), let L be the usual second-order elliptic operator associated with b(.) and \sigma(.). Under suitable…

Probability · Mathematics 2012-04-24 Weining Kang , Kavita Ramanan

In this note we define and study the stochastic process $X$ in link with a parabolic transmission operator $(A,D(A))$ in divergence form. The transmission operator involves a diffraction condition along a transmission boundary. To that aim…

Analysis of PDEs · Mathematics 2022-03-25 Pierre Etore , Miguel Martinez

We extend the Dirichlet principle to non-reversible Markov processes on countable state spaces. We present two variational formulas for the solution of the Poisson equation or, equivalently, for the capacity between two disjoint sets. As an…

Probability · Mathematics 2011-11-11 Alexandre Gaudillière , Claudio Landim

Motivated by entropic optimal transport, time reversal of diffusion processes is revisited. An integration by parts formula is derived for the carr\'e du champ of a Markov process in an abstract space. It leads to a time reversal formula…

Probability · Mathematics 2022-09-05 Patrick Cattiaux , Giovanni Conforti , Ivan Gentil , Christian Léonard

For a Markov process associated with a diffusion type Dirichlet form an upper bound is shown for the law of the finite dimensional distributions of the process. Under some more assumptions on the underlaying space this is also shown for the…

Probability · Mathematics 2009-07-28 Ann-Kathrin Jarecki

Let $E$ be a complete, separable metric space and $A$ be an operator on $C_b(E)$. We give an abstract definition of viscosity sub/supersolution of the resolvent equation $\lambda u-Au=h$ and show that, if the comparison principle holds,…

Probability · Mathematics 2015-11-19 Cristina Costantini , Thomas G. Kurtz

We provide a general construction scheme for $\mathcal L^p$-strong Feller processes on locally compact separable metric spaces. Starting from a regular Dirichlet form and specified regularity assumptions, we construct an associated…

Functional Analysis · Mathematics 2013-06-26 Benedict Baur , Martin Grothaus , Patrik Stilgenbauer

We consider the problem of learning two families of time-evolving random measures from indirect observations. In the first model, the signal is a Fleming--Viot diffusion, which is reversible with respect to the law of a Dirichlet process,…

Statistics Theory · Mathematics 2014-11-19 Omiros Papaspiliopoulos , Matteo Ruggiero , Dario Spanò

We consider a class of semi-Markov processes (SMP) such that the embedded discrete time Markov chain may be non-homogeneous. The corresponding augmented processes are represented as semi-martingales using stochastic integral equation…

Probability · Mathematics 2022-07-14 Anindya Goswami , Subhamay Saha , Ravishankar Kapildev Yadav

The diffraction of various random subsets of the integer lattice $\mathbb{Z}^{d}$, such as the coin tossing and related systems, are well understood. Here, we go one important step beyond and consider random point sets in $\mathbb{R}^{d}$.…

Mathematical Physics · Physics 2011-05-18 Michael Baake , Holger Koesters

The main objective consists in generalizing a well-known It{\^o} formula of J. Jacod and A. Shiryaev: given a c{\`a}dl{\`a}g process S, there is an equivalence between the fact that S is a semimartingale with given characteristics (B^k , C,…

Probability · Mathematics 2024-07-25 Elena Bandini , Francesco Russo

In this paper we explain that the natural filtration of a continuous Hunt process is continuous, and show that martingales over such a filtration are continuous. We further establish a martingale representation theorem for a class of…

Probability · Mathematics 2009-10-27 Zhongmin Qian , ; Jiangang Ying

This paper establishes explicit solutions for fractional diffusion problems on bounded domains. It also gives stochastic solutions, in terms of Markov processes time-changed by an inverse stable subordinator whose index equals the order of…

Probability · Mathematics 2016-04-22 Boris Baeumer , Tomasz Luks , Mark M. Meerschaert

The Markov chain approximation of a one-dimensional symmetric diffusion is investigated in this paper. Given an irreducible reflecting diffusion on a closed interval with scale function $s$ and speed measure $m$, the approximating Markov…

Probability · Mathematics 2020-04-16 Xiaodan Li , Jiangang Ying

We describe a procedure to introduce general dependence structures on a set of Dirichlet processes. Dependence can be in one direction to define a time series or in two directions to define spatial dependencies. More directions can also be…

Methodology · Statistics 2021-10-18 Luis E. Nieto-Barajas

We study diffusion processes driven by a Brownian motion with regular drift in a finite dimension setting. The drift has two components on different time scales, a fast conservative component and a slow dissipative component. Using the…

Probability · Mathematics 2014-03-27 Florent Barret , Max-K. Von Renesse

This paper explicitly computes the transition densities of a spectrally negative stable process with index greater than one, reflected at its infimum. First we derive the forward equation using the theory of sun-dual semigroups. The…

Probability · Mathematics 2016-11-28 Boris Baeumer , Mihály Kovács , Mark M. Meerschaert , René L. Schilling , Peter Straka

The $L^p$ maximal inequalities for martingales are one of the classical results in the theory of stochastic processes. Here we establish the sharp moderate maximal inequalities for one-dimensional diffusion processes, which include the…

Probability · Mathematics 2021-11-05 Xian Chen , Yong Chen , Mumien Cheng , Chen Jia

The study of both sensitivity analysis and differentiability of the stochastic flow of a reflected process in a convex polyhedral domain is challenging because the dynamics are discontinuous at the boundary of the domain and the boundary of…

Probability · Mathematics 2016-02-08 David Lipshutz , Kavita Ramanan

We investigate aspects of semimartingale decompositions, approximation and the martingale representation for multidimensional correlated Markov processes. A new interpretation of the dependence among processes is given using the martingale…

Statistics Theory · Mathematics 2015-02-24 Antonio Dalessandro , Gareth W. Peters