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Related papers: Pathwise Stochastic Calculus with Local Times

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Given a random time, we characterize the set of martingales for which the stopping theorems still hold. We also investigate how the stopping theorems are modified when we consider arbitrary random times. To this end, we introduce some…

Probability · Mathematics 2007-08-03 Ashkan Nikeghbali

In this article we are concerned with the study of the existence and uniqueness of pathwise mild solutions to evolutions equations driven by a H\"older continuous function with H\"older exponent in $(1/3,1/2)$. Our stochastic integral is a…

Analysis of PDEs · Mathematics 2016-08-10 María J. Garrido-Atienza , Kening Lu , Björn Schmalfuss

In this paper we study coupled fully non-local equations, where a linear non-local operator jointly acts on the time and space variables. We establish existence and uniqueness of the solution. A maximum principle is proved and used to…

Probability · Mathematics 2025-01-24 Giacomo Ascione , Enrico Scalas , Bruno Toaldo , Lorenzo Torricelli

In this paper we introduce the concept of conic martingales}. This class refers to stochastic processes having the martingale property, but that evolve within given (possibly time-dependent) boundaries. We first review some results about…

Probability · Mathematics 2016-03-25 Frédéric Vrins , Monique Jeanblanc

The notes are an overview of part of the theory of pathwise weak solutions to two classes of scalar fully nonlinear first- and second-order degenerate parabolic partial differential equations with multiplicative rough time dependence, a…

Analysis of PDEs · Mathematics 2019-09-12 Panagiotis E Souganidis

Study of stochastic differential equations on the field of p-adic numbers was initiated by the second author and has been developed by the first author, who proved several results for the p-adic case, similar to the theory of ordinary…

Probability · Mathematics 2007-08-14 Hiroshi Kaneko , Anatoly N. Kochubei

In this work we develop and apply a path integral formulation for the microscopic degrees of freedom obeying stochastic differential equations to an active Brownian particle (ABP) trapped in a harmonic potential. The formalism allows to…

Soft Condensed Matter · Physics 2025-10-01 Carsten Littek , Mike Brandt , Falko Ziebert

We show the existence of local and global in time weak martingale solutions for a stochastic version of the Othmer-Dunbar-Alt kinetic model of chemotaxis under suitable assumptions on the turning kernel and stochastic drift coefficients,…

Analysis of PDEs · Mathematics 2026-03-30 Benjamin Gess , Sebastian Herr , Anne Niesdroy

We study pathwise approximation of scalar stochastic differential equations at a single point. We provide the exact rate of convergence of the minimal errors that can be achieved by arbitrary numerical methods that are based (in a…

Probability · Mathematics 2007-05-23 Thomas Muller-Gronbach

In this paper we study the path-regularity and martingale properties of the set-valued stochastic integrals defined in our previous work Ararat et al. (2023). Such integrals have some fundamental differences from the well-known…

Probability · Mathematics 2023-08-28 Çağın Ararat , Jin Ma

In modeling multivariate time series, it is important to allow time-varying smoothness in the mean and covariance process. In particular, there may be certain time intervals exhibiting rapid changes and others in which changes are slow. If…

Applications · Statistics 2014-06-02 Daniele Durante , Bruno Scarpa , David B. Dunson

We consider additive functionals of stationary Markov processes and show that under Kipnis-Varadhan type conditions they converge in rough path topology to a Stratonovich Brownian motion, with a correction to the Levy area that can be…

Probability · Mathematics 2019-12-23 Jean-Dominique Deuschel , Tal Orenshtein , Nicolas Perkowski

In a wide range of applications, the stochastic properties of the observed time series change over time. The changes often occur gradually rather than abruptly: the properties are (approximately) constant for some time and then slowly start…

Methodology · Statistics 2015-04-03 Michael Vogt , Holger Dette

We consider the problem of tracking a target whose dynamics is modeled by a continuous It\=o semi-martingale. The aim is to minimize both deviation from the target and tracking efforts. We establish the existence of asymptotic lower bounds…

Probability · Mathematics 2015-10-16 Jiatu Cai , Mathieu Rosenbaum , Peter Tankov

Consider a class of null-recurrent randomly biased walks on a super-critical Gaton-Watson tree. We obtain the rates of convergence of the local times and the quenched local probability for the biased walk in the sub-diffusive case. These…

Probability · Mathematics 2019-01-03 Yueyun Hu

We construct superprocesses with dependent spatial motion (SDSMs) in Euclidean spaces $R^d$ with $d\ge1$ and show that,even when they start at some unbounded initial positive Radon measure such as Lebesgue measure on $R^d$, their local…

Probability · Mathematics 2022-05-23 Donald A. Dawson , Jean Vaillancourt , Hao Wang

We consider certain one dimensional ordinary stochastic differential equations driven by additive Brownian motion of variance $\varepsilon ^2$. When $\varepsilon =0$ such equations have an unstable non-hyperbolic fixed point and the drift…

Probability · Mathematics 2015-09-30 Giambattista Giacomin , Mathieu Merle

The persistence of a stochastic variable is the probability that it does not cross a given level during a fixed time interval. Although persistence is a simple concept to understand, it is in general hard to calculate. Here we consider zero…

Statistical Mechanics · Physics 2018-05-09 Markus Nyberg , Ludvig Lizana

We consider viscosity solutions of Hamilton-Jacobi equations with oscillatory spatial dependence and rough time dependence. The time dependence is in the form of the derivative of a continuous path that converges to a possibly…

Analysis of PDEs · Mathematics 2016-11-11 Benjamin Seeger

We study approximations of the partition function of dense graphical models. Partition functions of graphical models play a fundamental role is statistical physics, in statistics and in machine learning. Two of the main methods for…

Machine Learning · Computer Science 2018-02-21 Vishesh Jain , Frederic Koehler , Elchanan Mossel
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