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We propose a new multifractional stochastic process which allows for self-exciting behavior, similar to what can be seen for example in earthquakes and other self-organizing phenomena. The process can be seen as an extension of a…

Probability · Mathematics 2019-08-16 Fabian A. Harang , Marc Lagunas-Merino , Salvador Ortiz-Latorre

Approximation of the marginal distribution of the solution of the stochastic Navier-Stokes equations on the two-dimensional torus by high order numerical methods is considered. The corresponding rates of convergence are obtained for a…

Numerical Analysis · Mathematics 2011-05-16 Philipp Doersek

Local iterated function systems are an important generalisation of the standard (global) iterated function systems (IFSs). For a particular class of mappings, their fixed points are the graphs of local fractal functions and these functions…

Metric Geometry · Mathematics 2014-08-07 Michael F. Barnsley , Markus Hegland , Peter Massopust

The paper is devoted to three-parametric self-similar Gaussian Volterra processes that generalize fractional Brownian motion. We study the asymptotic growth of such processes and the properties of long- and short-range dependence. Then we…

Statistics Theory · Mathematics 2023-02-08 Yuliya Mishura , Kostiantyn Ralchenko , Sergiy Shklyar

A stochastic calculus is given for processes described by stochastic integrals with respect to fractional Brownian motions and Rosenblatt processes somewhat analogous to the stochastic calculus for It\^{o} processes. These processes for…

Probability · Mathematics 2019-08-02 Petr Čoupek , Tyrone E. Duncan , Bozenna Pasik-Duncan

In this note we analyze a model for a unidirectional unsteady flow of a viscous incompressible fluid with time dependent viscosity. A possible way to take into account such behaviour is to introduce a memory formalism, including thus the…

Analysis of PDEs · Mathematics 2013-04-04 Roberto Garra , Federico Polito

We define a fractional Ito stochastic integral with respect to a randomly scaled fractional Brownian motion via an $S$-transform approach. We investigate the properties of this stochastic integral, prove the Ito formula for functions of…

Probability · Mathematics 2026-03-05 Yana A. Butko , Merten Mlinarzik

We introduce a stochastic fractional calculus. As an application, we present a stochastic fractional calculus of variations, which generalizes the fractional calculus of variations to stochastic processes. A stochastic fractional…

Optimization and Control · Mathematics 2020-08-10 Houssine Zine , Delfim F. M. Torres

The `local time on curves' formula of Peskir provides a stochastic change of variables formula for a function whose derivatives may be discontinuous over a time-dependent curve, a setting which occurs often in applications in optimal…

Probability · Mathematics 2019-01-15 Daniel Wilson

In this paper we give an explicit expression for the local time of the classical risk process and associate it with the density of an occupational measure. To do so, we approximate the local time by a suitable sequence of absolutely…

Probability · Mathematics 2008-01-15 F. Cortes , J. A. León , J. Villa

We study the time-dependent Navier-Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion, and…

Numerical Analysis · Mathematics 2026-01-14 Bedřich Sousedík , Randy Price

We present a novel Kalman filter for spatiotemporal systems called the numerical Gaussian process Kalman filter (GPKF). Numerical Gaussian processes have recently been introduced as a physics informed machine learning method for simulating…

Systems and Control · Electrical Eng. & Systems 2021-05-06 Armin Küper , Steffen Waldherr

We consider stochastic differential equations driven by some Volterra processes. Under time reversal, these equations are transformed into past dependent stochastic differential equations driven by a standard Brownian motion. We are then in…

Probability · Mathematics 2012-12-24 Laurent Decreusefond

We define and study fractional versions of the well-known Gamma subordinator $\Gamma :=\{\Gamma (t),$ $t\geq 0\},$ which are obtained by time-changing $% \Gamma $ by means of an independent stable subordinator or its inverse. Their…

Probability · Mathematics 2013-05-09 Luisa Beghin

This paper analyzes a time-stepping discontinuous Galerkin method for fractional diffusion-wave problems. This method uses piecewise constant functions in the temporal discretization and continuous piecewise linear functions in the spatial…

Numerical Analysis · Mathematics 2019-08-27 Binjie Li , Tao Wang , Xiaoping Xie

In this work, we introduce a novel variational framework for the study of the unsteady Stokes equations in a bounded open Lipschitz domain in R^n, involving a Caputo fractional derivative in time. The nonlocal nature of the fractional…

Analysis of PDEs · Mathematics 2025-11-19 Juan Carlos Oyola Ballesteros , Paulo M. Carvalho-Neto

In the context of time-subordinated Brownian motion models, Fourier theory and methodology are proposed to modelling the stochastic distribution of time increments. Gaussian Variance-Mean mixtures and time-subordinated models are reviewed…

Mathematical Finance · Quantitative Finance 2025-10-21 Rohan Shenoy , Peter Kempthorne

Computation of moments of transformed random variables is a problem appearing in many engineering applications. The current methods for moment transformation are mostly based on the classical quadrature rules which cannot account for the…

Methodology · Statistics 2017-01-06 Jakub Prüher , Ondřej Straka

We establish estimates for the local and uniform moduli of continuity of the local time of multifractional Brownian motion, $B^H=(B^{H(t)}(t),t\in\mathbb{R}^+)$. An analogue of Chung's law of the iterated logarithm is studied for $B^H$ and…

Probability · Mathematics 2009-09-29 Brahim Boufoussi , Marco Dozzi , Raby Guerbaz

Stochastic processes play a fundamental role in physics, mathematics, engineering and finance. One potential application of quantum computation is to better approximate properties of stochastic processes. For example, quantum algorithms for…

Quantum Physics · Physics 2023-03-14 Adam Bouland , Aditi Dandapani , Anupam Prakash
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